{
 "cells": [
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "In this unit, we describe the procedure for training the stepping detector. Further, we present the classification result for stepping detector."
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "# Stepping detector"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 1,
   "metadata": {},
   "outputs": [],
   "source": [
    "'''Import and initialize MongoClient'''\n",
    "import subprocess\n",
    "import os\n",
    "import sys\n",
    "import json\n",
    "from pymongo import     MongoClient\n",
    "\n",
    "con = MongoClient()\n",
    "\n",
    "import pprint\n",
    "import numpy as np\n",
    "from pathlib import Path"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 2,
   "metadata": {},
   "outputs": [],
   "source": [
    "'''Import project specific library'''\n",
    "sys.path.append(os.path.join(os.getcwd(), 'LibCode'))\n",
    "import HAR_OrientetionIndependence\n",
    "import HARSaveToMongo\n",
    "import ComputeFeaturesTransportMode\n",
    "import FeaturesExtraction"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 3,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "<module 'FeaturesExtraction' from '/home/pruthvish/JRF/GitVersion_APTS_Software_Np/code/LibCode/FeaturesExtraction.py'>"
      ]
     },
     "execution_count": 3,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "'''For updating the lib changes effects'''\n",
    "import importlib\n",
    "importlib.reload(HAR_OrientetionIndependence)\n",
    "importlib.reload(HARSaveToMongo)\n",
    "importlib.reload(ComputeFeaturesTransportMode)\n",
    "importlib.reload(FeaturesExtraction)"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "## Save in MongoDB"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "The stepping detector is trained and validated on the Human Activity Recognition (HAR) data-set record [50]. The accelerometer record is stored in the `RouteName = HAR_DATASET_Preprocessing_And_HV` database of MongoDB. "
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "## Decomposition of accelerometer data\n",
    "The accelerometer record data is decomposed to `horizontal and vertical components` with the `IntervalLength` of `140 points.`"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 4,
   "metadata": {},
   "outputs": [],
   "source": [
    "def HAR_OrientetionIndependenceFunction(RouteName, IntervalLength):\n",
    "    \n",
    "    '''\n",
    "    input: The route name and dataset directory name\n",
    "    \n",
    "    output: None\n",
    "    \n",
    "    function: It fetches the data records placed in the specified data set directory \n",
    "    and save them in the MongoDB database. The function also computes the vertical and\n",
    "    horizontal accelerometer components and saves them in the MongoDB database. \n",
    "    '''        \n",
    "    \n",
    "    SingleTripsInfo = [LR['SingleTripInfo'] for LR in \n",
    "                       con[RouteName]['TripsInfo'].find({'ConvertedToEarthAxis':False})]\n",
    "\n",
    "    SingleTripsInfo = HAR_OrientetionIndependence.GetSingleTripRecord(SingleTripsInfo)\n",
    "\n",
    "    for (index,SingleTripInfo) in enumerate(SingleTripsInfo):\n",
    "        AcclMagRecordsListStoppages =[AclR for AclR in \n",
    "                                      con[RouteName][f'acc.{SingleTripInfo}.Raw'].find().sort([('index',1)])]\n",
    "        '''\n",
    "        print(AcclMagRecordsListStoppages)\n",
    "        input()\n",
    "        '''\n",
    "\n",
    "        HAR_OrientetionIndependence.ProcessEarthaxisHVComponentUsingJigSawMethod(\n",
    "            RouteName,SingleTripInfo, AcclMagRecordsListStoppages, IntervalLength)\n",
    "\n",
    "        print('Converting the accelerometer data to orientation independent record for SingleTripInfo')\n",
    "        print(SingleTripInfo)\n",
    "        con[RouteName]['TripsInfo'].update_one({'SingleTripInfo':f'acc.{SingleTripInfo}'},\n",
    "                                               {'$set':{'ConvertedToEarthAxis':True}})\n",
    "\n",
    "    #input()\n",
    "    #'''"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "## Features Extraction\n",
    "The feature `set-1 to set-4` are computed using the orientation independent horizontal and vertical components of accelerometer records for the window of `128 samples and 50% overlap`."
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 5,
   "metadata": {},
   "outputs": [],
   "source": [
    "def ComputeFeatures(RouteName, WindowList, WindowIndex, RecordType):\n",
    "    \n",
    "    '''\n",
    "    input: The WindowList and WindowIndex specify the window size for feature computation,\n",
    "    record type (Raw or Segment other than stoppage segment), and route name.\n",
    "    \n",
    "    output: None\n",
    "    \n",
    "    function: It extracts the appropriate accelerometer components from the MongoDB database based\n",
    "    on the provided input and computes the features on the windowed accelerometer component. The \n",
    "    computed features are stored in the MongoDB database.\n",
    "    '''\n",
    "    \n",
    "    SingleTripsInfo = [LR['SingleTripInfo'] for LR in \n",
    "                       con[RouteName]['TripsInfo'].find({'ConvertedToEarthAxis':True})]\n",
    "\n",
    "    SingleTripsInfo = HAR_OrientetionIndependence.GetSingleTripRecord(SingleTripsInfo)\n",
    "\n",
    "    for (index,SingleTripInfo) in enumerate(SingleTripsInfo):\n",
    "        HVComponent =[AclR for AclR in \n",
    "                      con[RouteName][SingleTripInfo+'.EAccHVComponent'].find(\n",
    "                      ).sort([('index',1)])]\n",
    "        ModeIntList = SingleTripInfo.split('.')\n",
    "        ModeInt = ActivityIncluded.index(ModeIntList[0])\n",
    "        #print(ModeIntList)\n",
    "        #input()\n",
    "        #'''\n",
    "        ComputeFeaturesTransportMode.ComputeFeature(SingleTripInfo,HVComponent,ModeInt,WindowList[WindowIndex],\n",
    "                                                    RecordType, RouteName)\n",
    "\n",
    "        FeaturesExtraction.ComputeFeatureForComponents(RouteName,HVComponent,ModeInt,\n",
    "                                                       WindowList[WindowIndex],SingleTripInfo,RecordType)\n",
    "        #'''\n",
    "        #print(SingleTripInfo)\n",
    "        #print(ModeInt)\n",
    "        print(SingleTripInfo)\n",
    "        #pprint.pprint(AcclMagRecordsListStoppages)\n",
    "        #input()\n"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 6,
   "metadata": {},
   "outputs": [],
   "source": [
    "def LoadInMongoFromNp(RouteName, NpPathDir):\n",
    "    \n",
    "    '''\n",
    "    input: The route name and numpy directory path\n",
    "    output: The MongoDB database collections from the Numpy files\n",
    "    function: It creates the MongoDB database of TripsInfo collections \n",
    "    and features collections from the Numpy files.\n",
    "    '''    \n",
    "    \n",
    "    CollectionName = 'TripsInfo'\n",
    "    TripsInfoRecords = np.load(f'{NpPathDir}/{RouteName}/{CollectionName}.npy', allow_pickle=True)\n",
    "    \n",
    "    print('Saving data in mongoDB')\n",
    "    print(RouteName, CollectionName)\n",
    "    con[RouteName][CollectionName].insert_many(TripsInfoRecords.tolist())\n",
    "    \n",
    "    CollectionNames = os.listdir(f'{NpPathDir}/{RouteName}')\n",
    "    #print(CollectionNames)\n",
    "    \n",
    "    CollectionNames_1 = [rec for rec in CollectionNames if '\\'.' not in rec] # To address the error\n",
    "    CollectionNames_2 = [rec for rec in CollectionNames if 'Feature' in rec]\n",
    "    \n",
    "    #print('Saving data in mongoDB')\n",
    "    for Collection in CollectionNames_2:\n",
    "        RecordsList = np.load(f'{NpPathDir}/{RouteName}/{Collection}', allow_pickle=True)\n",
    "        #print(Collection)\n",
    "        #pprint.pprint(RecordsList[0:3])\n",
    "        \n",
    "        CollectionName = Collection[0:-4]\n",
    "        \n",
    "        print(RouteName, CollectionName)\n",
    "        con[RouteName][CollectionName].insert_many(RecordsList.tolist())\n",
    "        \n",
    "    \n",
    "    \n",
    "def SaveInNp(RouteName, NpPathDir):\n",
    "    \n",
    "    '''\n",
    "    input: The route name and numpy directory path\n",
    "    output: Numpy files of the MongoDB database\n",
    "    function: It stores the Numpy files for the MongoDB database in the specified directory path\n",
    "    '''    \n",
    "    \n",
    "    CollectionNames = [Collection for Collection in \n",
    "                        con[RouteName].list_collection_names() if Collection!='system.indexes']\n",
    "\n",
    "    for CollectionName in CollectionNames:\n",
    "        print('CollectionName', CollectionName)\n",
    "        RecordsList = [rec for rec in con[RouteName][CollectionName].find().sort([('_id',1)])]\n",
    "\n",
    "        for RecordDict in RecordsList:\n",
    "            del[RecordDict['_id']]\n",
    "\n",
    "        if os.path.exists(os.path.join(NpPathDir, RouteName)) == False:\n",
    "            os.mkdir(os.path.join(NpPathDir, RouteName))\n",
    "\n",
    "            \n",
    "        #np.save(f'{Path}/{Database}/{CollectionName}.npy', RecordsList)\n",
    "        np.save(os.path.join(NpPathDir, RouteName,f'{CollectionName}.npy'), RecordsList)\n",
    "        "
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 7,
   "metadata": {},
   "outputs": [],
   "source": [
    "'''For directory management'''\n",
    "path = Path(os.getcwd())\n",
    "OneLevelUpPath = path.parents[0]"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 8,
   "metadata": {},
   "outputs": [],
   "source": [
    "'''Path for Np'''\n",
    "NpPathDir = os.path.join(str(OneLevelUpPath), 'data','NpData')"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "## Variables\n",
    "\n",
    "`ProjectDataUsed`: determines whether the project data or the user's own data is used for execution.\n",
    "\n",
    "`UsedPreTrained`: determines whether the pretrained and precomputed dataset or raw data is used for execution.\n",
    "\n",
    "`UseMongoDB`: determines whether the MonngoDB database or Numpy file is used for execution.\n",
    "\n",
    "`ReducedKFolds`: If false: one fold is used, else ten-fold is used"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 9,
   "metadata": {},
   "outputs": [],
   "source": [
    "'''\n",
    "ProjectDataUsed = True\n",
    "UsedPreTrained = True\n",
    "ReducedKFolds = False\n",
    "UseMongoDB = True\n",
    "'''\n",
    "\n",
    "#'''\n",
    "ProjectDataUsed = True\n",
    "UsedPreTrained = True\n",
    "ReducedKFolds = True\n",
    "UseMongoDB = False\n",
    "#'''\n",
    "\n",
    "'''\n",
    "ProjectDataUsed = True\n",
    "UsedPreTrained = False\n",
    "ReducedKFolds = False\n",
    "UseMongoDB = False\n",
    "'''"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "metadata": {},
   "outputs": [],
   "source": [
    "'''Variable initialization'''\n",
    "RouteName = 'Demo_HAR_DATASET_Preprocessing_And_HV'\n",
    "if ProjectDataUsed==True:\n",
    "    RecordDir = os.path.join(str(OneLevelUpPath), 'data','HAPTDataSet','RawData','')\n",
    "else:\n",
    "    RecordDir = os.path.join(str(OneLevelUpPath), 'data','UserData','HAPTDataSet','RawData','')\n",
    "IntervalLength = 140\n",
    "RecordType = '.Raw'"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 10,
   "metadata": {},
   "outputs": [],
   "source": [
    "WindowList = [32,64,128,256,512]\n",
    "WindowIndex = 2\n",
    "Activties = ['WALKING', 'WALKING_UPSTAIRS','WALKING_DOWNSTAIRS','SITTING','STANDING','LAYING',\n",
    "            'STAND_TO_SIT','SIT_TO_STAND','SIT_TO_LIE','LIE_TO_SIT','STAND_TO_LIE','LIE_TO_STAND']\n",
    "ActivityID = [1,2,3,4,5,6,7,8,9,10,11,12]\n",
    "ActivityIncluded = ['WALKING', 'WALKING_UPSTAIRS','WALKING_DOWNSTAIRS','SITTING','STANDING','LAYING',\n",
    "            'STAND_TO_SIT','SIT_TO_STAND','SIT_TO_LIE','LIE_TO_SIT','STAND_TO_LIE','LIE_TO_STAND']\n",
    "ActivityIncludedClassInt = [0,1,2,3,4]"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 11,
   "metadata": {},
   "outputs": [],
   "source": [
    "if UsedPreTrained==False and UseMongoDB==True:\n",
    "    \n",
    "    print('Reading data and saving in MongoDB')\n",
    "    HARSaveToMongo.SaveHARDataInMongo(RouteName, RecordDir)\n",
    "    print(f'Computing preprocessing for {RecordType} segments')\n",
    "    HAR_OrientetionIndependenceFunction(RouteName, IntervalLength)\n",
    "    print(f'Computing features for {RecordType} segments')\n",
    "    ComputeFeatures(RouteName, WindowList, WindowIndex, RecordType)\n",
    "    \n",
    "    \n",
    "    print('Saving MongoData in Np files')\n",
    "    SaveInNp(RouteName, NpPathDir)\n",
    "\n",
    "\n",
    "elif UseMongoDB==True:\n",
    "    RouteNamesListInDB = con.list_database_names()\n",
    "    if RouteName not in RouteNamesListInDB:\n",
    "        '''Load the data for RouteName, if RouteName is not in RouteNamesList'''\n",
    "        print('Loading MongoData from Np files')\n",
    "        LoadInMongoFromNp(RouteName, NpPathDir)\n",
    "    "
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 12,
   "metadata": {},
   "outputs": [],
   "source": [
    "#con.drop_database(RouteName)"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "## Classification "
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 13,
   "metadata": {},
   "outputs": [],
   "source": [
    "'''Import Libs'''\n",
    "from sklearn.model_selection import StratifiedKFold\n",
    "from sklearn.metrics import accuracy_score, confusion_matrix,precision_score, recall_score, f1_score\n",
    "from sklearn import tree\n",
    "from sklearn.svm import SVC\n",
    "from sklearn.preprocessing import StandardScaler\n",
    "from sklearn.ensemble import RandomForestClassifier\n",
    "from sklearn.linear_model import LogisticRegression\n",
    "from sklearn.naive_bayes import GaussianNB\n",
    "from collections import Counter\n",
    "from sklearn.impute import SimpleImputer\n",
    "\n",
    "'''Custom library'''\n",
    "import CAC_Helper\n",
    "import Stepper_Helper"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 14,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "<module 'Stepper_Helper' from '/home/pruthvish/JRF/GitVersion_APTS_Software_Np/code/LibCode/Stepper_Helper.py'>"
      ]
     },
     "execution_count": 14,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "'''For updating the lib changes effects'''\n",
    "import importlib\n",
    "importlib.reload(CAC_Helper)\n",
    "importlib.reload(Stepper_Helper)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 15,
   "metadata": {},
   "outputs": [],
   "source": [
    "'''Variables for Classification'''\n",
    "ResultPathDir = os.path.join(str(OneLevelUpPath), 'results','SteppingDetector','')\n",
    "\n",
    "\n",
    "if os.path.exists(ResultPathDir) == False:\n",
    "    os.mkdir(ResultPathDir)\n",
    "\n",
    "TrainedModelPathDir = os.path.join(str(OneLevelUpPath), 'data', 'TrainedModel','SteppingDetector','')\n",
    "\n",
    "'''Any one route type as decided by Stoppage experiment'''\n",
    "#RecordType = '.SegmentOtherThanStoppage'\n",
    "#RecordType = '.StoppageSegment'\n",
    "RecordType = '.Raw'\n",
    "\n",
    "ClassifierList = [GaussianNB(), LogisticRegression(random_state=0), \n",
    "                  RandomForestClassifier(max_depth=20), tree.DecisionTreeClassifier(), \n",
    "                  SVC(gamma='auto')\n",
    "                 ]\n",
    "ClassifierNameList = ['NB', 'LogisticRegression', 'RF', 'DT', 'SVC']\n",
    "\n",
    "Index = 3\n",
    "\n",
    "Classifier = ClassifierList[Index]\n",
    "ClassifierName = ClassifierNameList[Index]"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 16,
   "metadata": {},
   "outputs": [],
   "source": [
    "def ApplyClassification(Classes, FeatureType, RecordType, SelectedFeatures, SelectedFeaturesFlag,\n",
    "                        Classifier, ClassifierName, ResultPathDir, ProjectDataUsed, RouteName, \n",
    "                        UsedPreTrained, ClassifierName_ForModelSave, TrainedModelPathDir, ReducedKFolds,\n",
    "                        NpPathDir, UseMongoDB\n",
    "                       ):\n",
    "    \n",
    "    '''\n",
    "    input: \n",
    "        Classes: The number of classes\n",
    "        \n",
    "        FeatureType and RecordType: feature type and record type information\n",
    "        \n",
    "        SelectedFeatures and SelectedFeaturesFlag: selected features list and flag to \n",
    "        determine if selected features are list is used\n",
    "        \n",
    "        Classifier and ClassifierName: classifier object variable and classifier name\n",
    "        \n",
    "        ResultPathDir: path of result directory\n",
    "        \n",
    "        ProjectDataUsed: flag to determine whether the project dataset or user dataset is used\n",
    "        \n",
    "        RouteNameTestList: The route names list to be considered during classification\n",
    "        \n",
    "        UsedPreTrained: Flag to determine whether the pretrained classifier should be used\n",
    "        or the classifier is to be trained\n",
    "        \n",
    "        ClassifierName_ForModelSave: the name of classifier for saving a model\n",
    "        \n",
    "        TrainedModelPathDir: path of trainedModel directory \n",
    "    \n",
    "    output: None\n",
    "    \n",
    "    function: It trains and validates the classifier the ten-fold cross-validation with stratified\n",
    "    sampling of each class. The performance metrics of the classifier is stores as a txt file in the\n",
    "    result directory\n",
    "    \n",
    "    '''        \n",
    "    \n",
    "    MetricsDict = CAC_Helper.InitializeMetricsDict(Classes)\n",
    "    \n",
    "    #SelectedFeatures = []\n",
    "    \n",
    "    if UseMongoDB==True:\n",
    "        #X, y = Stepper_Helper.GetFeaturesFromMongoDB(RouteName, FeatureType, RecordType)\n",
    "        X, y = Stepper_Helper.GetFeaturesFromMongoDB(RouteName, FeatureType, RecordType, \n",
    "                                                     SelectedFeatures, SelectedFeaturesFlag)\n",
    "        \n",
    "        \n",
    "        if os.path.exists(os.path.join(NpPathDir,'SteppingDetector'))==False:\n",
    "            os.mkdir(os.path.join(NpPathDir,'SteppingDetector'))\n",
    "            \n",
    "        np.save(f'{NpPathDir}/SteppingDetector/X_{FeatureType}_{RecordType}_{SelectedFeaturesFlag}.npy', X)\n",
    "        np.save(f'{NpPathDir}/SteppingDetector/y_{FeatureType}_{RecordType}_{SelectedFeaturesFlag}.npy', y)\n",
    "\n",
    "    else:\n",
    "        X = np.load(f'{NpPathDir}/SteppingDetector/X_{FeatureType}_{RecordType}_{SelectedFeaturesFlag}.npy',\n",
    "                    allow_pickle=True)\n",
    "        y = np.load(f'{NpPathDir}/SteppingDetector/y_{FeatureType}_{RecordType}_{SelectedFeaturesFlag}.npy',\n",
    "                    allow_pickle=True)\n",
    "    \n",
    "    \n",
    "    MetricsDict = CAC_Helper.TrainAndPredict(X, y, Classifier, MetricsDict, ResultPathDir,\n",
    "                                             ClassifierName, UsedPreTrained, \n",
    "                                             ClassifierName_ForModelSave, TrainedModelPathDir, ReducedKFolds)\n",
    "    \n",
    "    CAC_Helper.PrintMetricsDict(ClassifierName, ResultPathDir, FeatureType, RecordType, \n",
    "                                SelectedFeaturesFlag, MetricsDict)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 17,
   "metadata": {},
   "outputs": [],
   "source": [
    "Classes = 5"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 19,
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "Classifier, ClassifierName GaussianNB() NB\n",
      "Feature set-1\n"
     ]
    },
    {
     "name": "stderr",
     "output_type": "stream",
     "text": [
      "/home/pruthvish/JRF/RoadNetwork/RoadNetwork_VirtualEnv/lib/python3.8/site-packages/sklearn/metrics/_classification.py:1334: UndefinedMetricWarning: Precision is ill-defined and being set to 0.0 in labels with no predicted samples. Use `zero_division` parameter to control this behavior.\n",
      "  _warn_prf(average, modifier, msg_start, len(result))\n",
      "/home/pruthvish/JRF/RoadNetwork/RoadNetwork_VirtualEnv/lib/python3.8/site-packages/sklearn/metrics/_classification.py:1334: UndefinedMetricWarning: Recall is ill-defined and being set to 0.0 in labels with no true samples. Use `zero_division` parameter to control this behavior.\n",
      "  _warn_prf(average, modifier, msg_start, len(result))\n",
      "/home/pruthvish/JRF/RoadNetwork/RoadNetwork_VirtualEnv/lib/python3.8/site-packages/sklearn/metrics/_classification.py:1599: UndefinedMetricWarning: F-score is ill-defined and being set to 0.0 in labels with no true nor predicted samples. Use `zero_division` parameter to control this behavior.\n",
      "  _warn_prf(average, \"true nor predicted\", \"F-score is\", len(true_sum))\n",
      "/home/pruthvish/JRF/RoadNetwork/RoadNetwork_VirtualEnv/lib/python3.8/site-packages/sklearn/metrics/_classification.py:1334: UndefinedMetricWarning: Precision is ill-defined and being set to 0.0 in labels with no predicted samples. Use `zero_division` parameter to control this behavior.\n",
      "  _warn_prf(average, modifier, msg_start, len(result))\n",
      "/home/pruthvish/JRF/RoadNetwork/RoadNetwork_VirtualEnv/lib/python3.8/site-packages/sklearn/metrics/_classification.py:1334: UndefinedMetricWarning: Recall is ill-defined and being set to 0.0 in labels with no true samples. Use `zero_division` parameter to control this behavior.\n",
      "  _warn_prf(average, modifier, msg_start, len(result))\n",
      "/home/pruthvish/JRF/RoadNetwork/RoadNetwork_VirtualEnv/lib/python3.8/site-packages/sklearn/metrics/_classification.py:1599: UndefinedMetricWarning: F-score is ill-defined and being set to 0.0 in labels with no true nor predicted samples. Use `zero_division` parameter to control this behavior.\n",
      "  _warn_prf(average, \"true nor predicted\", \"F-score is\", len(true_sum))\n",
      "/home/pruthvish/JRF/RoadNetwork/RoadNetwork_VirtualEnv/lib/python3.8/site-packages/sklearn/metrics/_classification.py:1334: UndefinedMetricWarning: Precision is ill-defined and being set to 0.0 in labels with no predicted samples. Use `zero_division` parameter to control this behavior.\n",
      "  _warn_prf(average, modifier, msg_start, len(result))\n",
      "/home/pruthvish/JRF/RoadNetwork/RoadNetwork_VirtualEnv/lib/python3.8/site-packages/sklearn/metrics/_classification.py:1334: UndefinedMetricWarning: Recall is ill-defined and being set to 0.0 in labels with no true samples. Use `zero_division` parameter to control this behavior.\n",
      "  _warn_prf(average, modifier, msg_start, len(result))\n",
      "/home/pruthvish/JRF/RoadNetwork/RoadNetwork_VirtualEnv/lib/python3.8/site-packages/sklearn/metrics/_classification.py:1599: UndefinedMetricWarning: F-score is ill-defined and being set to 0.0 in labels with no true nor predicted samples. Use `zero_division` parameter to control this behavior.\n",
      "  _warn_prf(average, \"true nor predicted\", \"F-score is\", len(true_sum))\n",
      "/home/pruthvish/JRF/RoadNetwork/RoadNetwork_VirtualEnv/lib/python3.8/site-packages/sklearn/metrics/_classification.py:1334: UndefinedMetricWarning: Precision is ill-defined and being set to 0.0 in labels with no predicted samples. Use `zero_division` parameter to control this behavior.\n",
      "  _warn_prf(average, modifier, msg_start, len(result))\n",
      "/home/pruthvish/JRF/RoadNetwork/RoadNetwork_VirtualEnv/lib/python3.8/site-packages/sklearn/metrics/_classification.py:1334: UndefinedMetricWarning: Recall is ill-defined and being set to 0.0 in labels with no true samples. Use `zero_division` parameter to control this behavior.\n",
      "  _warn_prf(average, modifier, msg_start, len(result))\n",
      "/home/pruthvish/JRF/RoadNetwork/RoadNetwork_VirtualEnv/lib/python3.8/site-packages/sklearn/metrics/_classification.py:1599: UndefinedMetricWarning: F-score is ill-defined and being set to 0.0 in labels with no true nor predicted samples. Use `zero_division` parameter to control this behavior.\n",
      "  _warn_prf(average, \"true nor predicted\", \"F-score is\", len(true_sum))\n",
      "/home/pruthvish/JRF/RoadNetwork/RoadNetwork_VirtualEnv/lib/python3.8/site-packages/sklearn/metrics/_classification.py:1334: UndefinedMetricWarning: Precision is ill-defined and being set to 0.0 in labels with no predicted samples. Use `zero_division` parameter to control this behavior.\n",
      "  _warn_prf(average, modifier, msg_start, len(result))\n",
      "/home/pruthvish/JRF/RoadNetwork/RoadNetwork_VirtualEnv/lib/python3.8/site-packages/sklearn/metrics/_classification.py:1334: UndefinedMetricWarning: Recall is ill-defined and being set to 0.0 in labels with no true samples. Use `zero_division` parameter to control this behavior.\n",
      "  _warn_prf(average, modifier, msg_start, len(result))\n",
      "/home/pruthvish/JRF/RoadNetwork/RoadNetwork_VirtualEnv/lib/python3.8/site-packages/sklearn/metrics/_classification.py:1599: UndefinedMetricWarning: F-score is ill-defined and being set to 0.0 in labels with no true nor predicted samples. Use `zero_division` parameter to control this behavior.\n",
      "  _warn_prf(average, \"true nor predicted\", \"F-score is\", len(true_sum))\n",
      "/home/pruthvish/JRF/RoadNetwork/RoadNetwork_VirtualEnv/lib/python3.8/site-packages/sklearn/metrics/_classification.py:1334: UndefinedMetricWarning: Precision is ill-defined and being set to 0.0 in labels with no predicted samples. Use `zero_division` parameter to control this behavior.\n",
      "  _warn_prf(average, modifier, msg_start, len(result))\n",
      "/home/pruthvish/JRF/RoadNetwork/RoadNetwork_VirtualEnv/lib/python3.8/site-packages/sklearn/metrics/_classification.py:1334: UndefinedMetricWarning: Recall is ill-defined and being set to 0.0 in labels with no true samples. Use `zero_division` parameter to control this behavior.\n",
      "  _warn_prf(average, modifier, msg_start, len(result))\n",
      "/home/pruthvish/JRF/RoadNetwork/RoadNetwork_VirtualEnv/lib/python3.8/site-packages/sklearn/metrics/_classification.py:1599: UndefinedMetricWarning: F-score is ill-defined and being set to 0.0 in labels with no true nor predicted samples. Use `zero_division` parameter to control this behavior.\n",
      "  _warn_prf(average, \"true nor predicted\", \"F-score is\", len(true_sum))\n",
      "/home/pruthvish/JRF/RoadNetwork/RoadNetwork_VirtualEnv/lib/python3.8/site-packages/sklearn/metrics/_classification.py:1334: UndefinedMetricWarning: Precision is ill-defined and being set to 0.0 in labels with no predicted samples. Use `zero_division` parameter to control this behavior.\n",
      "  _warn_prf(average, modifier, msg_start, len(result))\n",
      "/home/pruthvish/JRF/RoadNetwork/RoadNetwork_VirtualEnv/lib/python3.8/site-packages/sklearn/metrics/_classification.py:1334: UndefinedMetricWarning: Recall is ill-defined and being set to 0.0 in labels with no true samples. Use `zero_division` parameter to control this behavior.\n",
      "  _warn_prf(average, modifier, msg_start, len(result))\n",
      "/home/pruthvish/JRF/RoadNetwork/RoadNetwork_VirtualEnv/lib/python3.8/site-packages/sklearn/metrics/_classification.py:1599: UndefinedMetricWarning: F-score is ill-defined and being set to 0.0 in labels with no true nor predicted samples. Use `zero_division` parameter to control this behavior.\n",
      "  _warn_prf(average, \"true nor predicted\", \"F-score is\", len(true_sum))\n",
      "/home/pruthvish/JRF/RoadNetwork/RoadNetwork_VirtualEnv/lib/python3.8/site-packages/sklearn/metrics/_classification.py:1334: UndefinedMetricWarning: Precision is ill-defined and being set to 0.0 in labels with no predicted samples. Use `zero_division` parameter to control this behavior.\n",
      "  _warn_prf(average, modifier, msg_start, len(result))\n",
      "/home/pruthvish/JRF/RoadNetwork/RoadNetwork_VirtualEnv/lib/python3.8/site-packages/sklearn/metrics/_classification.py:1334: UndefinedMetricWarning: Recall is ill-defined and being set to 0.0 in labels with no true samples. Use `zero_division` parameter to control this behavior.\n",
      "  _warn_prf(average, modifier, msg_start, len(result))\n",
      "/home/pruthvish/JRF/RoadNetwork/RoadNetwork_VirtualEnv/lib/python3.8/site-packages/sklearn/metrics/_classification.py:1599: UndefinedMetricWarning: F-score is ill-defined and being set to 0.0 in labels with no true nor predicted samples. Use `zero_division` parameter to control this behavior.\n",
      "  _warn_prf(average, \"true nor predicted\", \"F-score is\", len(true_sum))\n",
      "/home/pruthvish/JRF/RoadNetwork/RoadNetwork_VirtualEnv/lib/python3.8/site-packages/sklearn/metrics/_classification.py:1334: UndefinedMetricWarning: Precision is ill-defined and being set to 0.0 in labels with no predicted samples. Use `zero_division` parameter to control this behavior.\n",
      "  _warn_prf(average, modifier, msg_start, len(result))\n",
      "/home/pruthvish/JRF/RoadNetwork/RoadNetwork_VirtualEnv/lib/python3.8/site-packages/sklearn/metrics/_classification.py:1334: UndefinedMetricWarning: Recall is ill-defined and being set to 0.0 in labels with no true samples. Use `zero_division` parameter to control this behavior.\n",
      "  _warn_prf(average, modifier, msg_start, len(result))\n",
      "/home/pruthvish/JRF/RoadNetwork/RoadNetwork_VirtualEnv/lib/python3.8/site-packages/sklearn/metrics/_classification.py:1599: UndefinedMetricWarning: F-score is ill-defined and being set to 0.0 in labels with no true nor predicted samples. Use `zero_division` parameter to control this behavior.\n",
      "  _warn_prf(average, \"true nor predicted\", \"F-score is\", len(true_sum))\n",
      "/home/pruthvish/JRF/RoadNetwork/RoadNetwork_VirtualEnv/lib/python3.8/site-packages/sklearn/metrics/_classification.py:1334: UndefinedMetricWarning: Precision is ill-defined and being set to 0.0 in labels with no predicted samples. Use `zero_division` parameter to control this behavior.\n",
      "  _warn_prf(average, modifier, msg_start, len(result))\n",
      "/home/pruthvish/JRF/RoadNetwork/RoadNetwork_VirtualEnv/lib/python3.8/site-packages/sklearn/metrics/_classification.py:1334: UndefinedMetricWarning: Recall is ill-defined and being set to 0.0 in labels with no true samples. Use `zero_division` parameter to control this behavior.\n",
      "  _warn_prf(average, modifier, msg_start, len(result))\n",
      "/home/pruthvish/JRF/RoadNetwork/RoadNetwork_VirtualEnv/lib/python3.8/site-packages/sklearn/metrics/_classification.py:1599: UndefinedMetricWarning: F-score is ill-defined and being set to 0.0 in labels with no true nor predicted samples. Use `zero_division` parameter to control this behavior.\n",
      "  _warn_prf(average, \"true nor predicted\", \"F-score is\", len(true_sum))\n"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "Feature set-2\n"
     ]
    },
    {
     "name": "stderr",
     "output_type": "stream",
     "text": [
      "/home/pruthvish/JRF/RoadNetwork/RoadNetwork_VirtualEnv/lib/python3.8/site-packages/sklearn/metrics/_classification.py:1334: UndefinedMetricWarning: Precision is ill-defined and being set to 0.0 in labels with no predicted samples. Use `zero_division` parameter to control this behavior.\n",
      "  _warn_prf(average, modifier, msg_start, len(result))\n",
      "/home/pruthvish/JRF/RoadNetwork/RoadNetwork_VirtualEnv/lib/python3.8/site-packages/sklearn/metrics/_classification.py:1334: UndefinedMetricWarning: Recall is ill-defined and being set to 0.0 in labels with no true samples. Use `zero_division` parameter to control this behavior.\n",
      "  _warn_prf(average, modifier, msg_start, len(result))\n",
      "/home/pruthvish/JRF/RoadNetwork/RoadNetwork_VirtualEnv/lib/python3.8/site-packages/sklearn/metrics/_classification.py:1599: UndefinedMetricWarning: F-score is ill-defined and being set to 0.0 in labels with no true nor predicted samples. Use `zero_division` parameter to control this behavior.\n",
      "  _warn_prf(average, \"true nor predicted\", \"F-score is\", len(true_sum))\n",
      "/home/pruthvish/JRF/RoadNetwork/RoadNetwork_VirtualEnv/lib/python3.8/site-packages/sklearn/metrics/_classification.py:1334: UndefinedMetricWarning: Precision is ill-defined and being set to 0.0 in labels with no predicted samples. Use `zero_division` parameter to control this behavior.\n",
      "  _warn_prf(average, modifier, msg_start, len(result))\n",
      "/home/pruthvish/JRF/RoadNetwork/RoadNetwork_VirtualEnv/lib/python3.8/site-packages/sklearn/metrics/_classification.py:1334: UndefinedMetricWarning: Recall is ill-defined and being set to 0.0 in labels with no true samples. Use `zero_division` parameter to control this behavior.\n",
      "  _warn_prf(average, modifier, msg_start, len(result))\n",
      "/home/pruthvish/JRF/RoadNetwork/RoadNetwork_VirtualEnv/lib/python3.8/site-packages/sklearn/metrics/_classification.py:1599: UndefinedMetricWarning: F-score is ill-defined and being set to 0.0 in labels with no true nor predicted samples. Use `zero_division` parameter to control this behavior.\n",
      "  _warn_prf(average, \"true nor predicted\", \"F-score is\", len(true_sum))\n",
      "/home/pruthvish/JRF/RoadNetwork/RoadNetwork_VirtualEnv/lib/python3.8/site-packages/sklearn/metrics/_classification.py:1334: UndefinedMetricWarning: Precision is ill-defined and being set to 0.0 in labels with no predicted samples. Use `zero_division` parameter to control this behavior.\n",
      "  _warn_prf(average, modifier, msg_start, len(result))\n",
      "/home/pruthvish/JRF/RoadNetwork/RoadNetwork_VirtualEnv/lib/python3.8/site-packages/sklearn/metrics/_classification.py:1334: UndefinedMetricWarning: Recall is ill-defined and being set to 0.0 in labels with no true samples. Use `zero_division` parameter to control this behavior.\n",
      "  _warn_prf(average, modifier, msg_start, len(result))\n",
      "/home/pruthvish/JRF/RoadNetwork/RoadNetwork_VirtualEnv/lib/python3.8/site-packages/sklearn/metrics/_classification.py:1599: UndefinedMetricWarning: F-score is ill-defined and being set to 0.0 in labels with no true nor predicted samples. Use `zero_division` parameter to control this behavior.\n",
      "  _warn_prf(average, \"true nor predicted\", \"F-score is\", len(true_sum))\n",
      "/home/pruthvish/JRF/RoadNetwork/RoadNetwork_VirtualEnv/lib/python3.8/site-packages/sklearn/metrics/_classification.py:1334: UndefinedMetricWarning: Precision is ill-defined and being set to 0.0 in labels with no predicted samples. Use `zero_division` parameter to control this behavior.\n",
      "  _warn_prf(average, modifier, msg_start, len(result))\n",
      "/home/pruthvish/JRF/RoadNetwork/RoadNetwork_VirtualEnv/lib/python3.8/site-packages/sklearn/metrics/_classification.py:1334: UndefinedMetricWarning: Recall is ill-defined and being set to 0.0 in labels with no true samples. Use `zero_division` parameter to control this behavior.\n",
      "  _warn_prf(average, modifier, msg_start, len(result))\n",
      "/home/pruthvish/JRF/RoadNetwork/RoadNetwork_VirtualEnv/lib/python3.8/site-packages/sklearn/metrics/_classification.py:1599: UndefinedMetricWarning: F-score is ill-defined and being set to 0.0 in labels with no true nor predicted samples. Use `zero_division` parameter to control this behavior.\n",
      "  _warn_prf(average, \"true nor predicted\", \"F-score is\", len(true_sum))\n",
      "/home/pruthvish/JRF/RoadNetwork/RoadNetwork_VirtualEnv/lib/python3.8/site-packages/sklearn/metrics/_classification.py:1334: UndefinedMetricWarning: Precision is ill-defined and being set to 0.0 in labels with no predicted samples. Use `zero_division` parameter to control this behavior.\n",
      "  _warn_prf(average, modifier, msg_start, len(result))\n",
      "/home/pruthvish/JRF/RoadNetwork/RoadNetwork_VirtualEnv/lib/python3.8/site-packages/sklearn/metrics/_classification.py:1334: UndefinedMetricWarning: Recall is ill-defined and being set to 0.0 in labels with no true samples. Use `zero_division` parameter to control this behavior.\n",
      "  _warn_prf(average, modifier, msg_start, len(result))\n",
      "/home/pruthvish/JRF/RoadNetwork/RoadNetwork_VirtualEnv/lib/python3.8/site-packages/sklearn/metrics/_classification.py:1599: UndefinedMetricWarning: F-score is ill-defined and being set to 0.0 in labels with no true nor predicted samples. Use `zero_division` parameter to control this behavior.\n",
      "  _warn_prf(average, \"true nor predicted\", \"F-score is\", len(true_sum))\n",
      "/home/pruthvish/JRF/RoadNetwork/RoadNetwork_VirtualEnv/lib/python3.8/site-packages/sklearn/metrics/_classification.py:1334: UndefinedMetricWarning: Precision is ill-defined and being set to 0.0 in labels with no predicted samples. Use `zero_division` parameter to control this behavior.\n",
      "  _warn_prf(average, modifier, msg_start, len(result))\n",
      "/home/pruthvish/JRF/RoadNetwork/RoadNetwork_VirtualEnv/lib/python3.8/site-packages/sklearn/metrics/_classification.py:1334: UndefinedMetricWarning: Recall is ill-defined and being set to 0.0 in labels with no true samples. Use `zero_division` parameter to control this behavior.\n",
      "  _warn_prf(average, modifier, msg_start, len(result))\n",
      "/home/pruthvish/JRF/RoadNetwork/RoadNetwork_VirtualEnv/lib/python3.8/site-packages/sklearn/metrics/_classification.py:1599: UndefinedMetricWarning: F-score is ill-defined and being set to 0.0 in labels with no true nor predicted samples. Use `zero_division` parameter to control this behavior.\n",
      "  _warn_prf(average, \"true nor predicted\", \"F-score is\", len(true_sum))\n",
      "/home/pruthvish/JRF/RoadNetwork/RoadNetwork_VirtualEnv/lib/python3.8/site-packages/sklearn/metrics/_classification.py:1334: UndefinedMetricWarning: Precision is ill-defined and being set to 0.0 in labels with no predicted samples. Use `zero_division` parameter to control this behavior.\n",
      "  _warn_prf(average, modifier, msg_start, len(result))\n",
      "/home/pruthvish/JRF/RoadNetwork/RoadNetwork_VirtualEnv/lib/python3.8/site-packages/sklearn/metrics/_classification.py:1334: UndefinedMetricWarning: Recall is ill-defined and being set to 0.0 in labels with no true samples. Use `zero_division` parameter to control this behavior.\n",
      "  _warn_prf(average, modifier, msg_start, len(result))\n",
      "/home/pruthvish/JRF/RoadNetwork/RoadNetwork_VirtualEnv/lib/python3.8/site-packages/sklearn/metrics/_classification.py:1599: UndefinedMetricWarning: F-score is ill-defined and being set to 0.0 in labels with no true nor predicted samples. Use `zero_division` parameter to control this behavior.\n",
      "  _warn_prf(average, \"true nor predicted\", \"F-score is\", len(true_sum))\n",
      "/home/pruthvish/JRF/RoadNetwork/RoadNetwork_VirtualEnv/lib/python3.8/site-packages/sklearn/metrics/_classification.py:1334: UndefinedMetricWarning: Precision is ill-defined and being set to 0.0 in labels with no predicted samples. Use `zero_division` parameter to control this behavior.\n",
      "  _warn_prf(average, modifier, msg_start, len(result))\n",
      "/home/pruthvish/JRF/RoadNetwork/RoadNetwork_VirtualEnv/lib/python3.8/site-packages/sklearn/metrics/_classification.py:1334: UndefinedMetricWarning: Recall is ill-defined and being set to 0.0 in labels with no true samples. Use `zero_division` parameter to control this behavior.\n",
      "  _warn_prf(average, modifier, msg_start, len(result))\n",
      "/home/pruthvish/JRF/RoadNetwork/RoadNetwork_VirtualEnv/lib/python3.8/site-packages/sklearn/metrics/_classification.py:1599: UndefinedMetricWarning: F-score is ill-defined and being set to 0.0 in labels with no true nor predicted samples. Use `zero_division` parameter to control this behavior.\n",
      "  _warn_prf(average, \"true nor predicted\", \"F-score is\", len(true_sum))\n",
      "/home/pruthvish/JRF/RoadNetwork/RoadNetwork_VirtualEnv/lib/python3.8/site-packages/sklearn/metrics/_classification.py:1334: UndefinedMetricWarning: Precision is ill-defined and being set to 0.0 in labels with no predicted samples. Use `zero_division` parameter to control this behavior.\n",
      "  _warn_prf(average, modifier, msg_start, len(result))\n",
      "/home/pruthvish/JRF/RoadNetwork/RoadNetwork_VirtualEnv/lib/python3.8/site-packages/sklearn/metrics/_classification.py:1334: UndefinedMetricWarning: Recall is ill-defined and being set to 0.0 in labels with no true samples. Use `zero_division` parameter to control this behavior.\n",
      "  _warn_prf(average, modifier, msg_start, len(result))\n",
      "/home/pruthvish/JRF/RoadNetwork/RoadNetwork_VirtualEnv/lib/python3.8/site-packages/sklearn/metrics/_classification.py:1599: UndefinedMetricWarning: F-score is ill-defined and being set to 0.0 in labels with no true nor predicted samples. Use `zero_division` parameter to control this behavior.\n",
      "  _warn_prf(average, \"true nor predicted\", \"F-score is\", len(true_sum))\n",
      "/home/pruthvish/JRF/RoadNetwork/RoadNetwork_VirtualEnv/lib/python3.8/site-packages/sklearn/metrics/_classification.py:1334: UndefinedMetricWarning: Precision is ill-defined and being set to 0.0 in labels with no predicted samples. Use `zero_division` parameter to control this behavior.\n",
      "  _warn_prf(average, modifier, msg_start, len(result))\n",
      "/home/pruthvish/JRF/RoadNetwork/RoadNetwork_VirtualEnv/lib/python3.8/site-packages/sklearn/metrics/_classification.py:1334: UndefinedMetricWarning: Recall is ill-defined and being set to 0.0 in labels with no true samples. Use `zero_division` parameter to control this behavior.\n",
      "  _warn_prf(average, modifier, msg_start, len(result))\n",
      "/home/pruthvish/JRF/RoadNetwork/RoadNetwork_VirtualEnv/lib/python3.8/site-packages/sklearn/metrics/_classification.py:1599: UndefinedMetricWarning: F-score is ill-defined and being set to 0.0 in labels with no true nor predicted samples. Use `zero_division` parameter to control this behavior.\n",
      "  _warn_prf(average, \"true nor predicted\", \"F-score is\", len(true_sum))\n"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "Feature set-3\n"
     ]
    },
    {
     "name": "stderr",
     "output_type": "stream",
     "text": [
      "/home/pruthvish/JRF/RoadNetwork/RoadNetwork_VirtualEnv/lib/python3.8/site-packages/sklearn/metrics/_classification.py:1334: UndefinedMetricWarning: Precision is ill-defined and being set to 0.0 in labels with no predicted samples. Use `zero_division` parameter to control this behavior.\n",
      "  _warn_prf(average, modifier, msg_start, len(result))\n",
      "/home/pruthvish/JRF/RoadNetwork/RoadNetwork_VirtualEnv/lib/python3.8/site-packages/sklearn/metrics/_classification.py:1334: UndefinedMetricWarning: Recall is ill-defined and being set to 0.0 in labels with no true samples. Use `zero_division` parameter to control this behavior.\n",
      "  _warn_prf(average, modifier, msg_start, len(result))\n",
      "/home/pruthvish/JRF/RoadNetwork/RoadNetwork_VirtualEnv/lib/python3.8/site-packages/sklearn/metrics/_classification.py:1599: UndefinedMetricWarning: F-score is ill-defined and being set to 0.0 in labels with no true nor predicted samples. Use `zero_division` parameter to control this behavior.\n",
      "  _warn_prf(average, \"true nor predicted\", \"F-score is\", len(true_sum))\n",
      "/home/pruthvish/JRF/RoadNetwork/RoadNetwork_VirtualEnv/lib/python3.8/site-packages/sklearn/metrics/_classification.py:1334: UndefinedMetricWarning: Precision is ill-defined and being set to 0.0 in labels with no predicted samples. Use `zero_division` parameter to control this behavior.\n",
      "  _warn_prf(average, modifier, msg_start, len(result))\n",
      "/home/pruthvish/JRF/RoadNetwork/RoadNetwork_VirtualEnv/lib/python3.8/site-packages/sklearn/metrics/_classification.py:1334: UndefinedMetricWarning: Recall is ill-defined and being set to 0.0 in labels with no true samples. Use `zero_division` parameter to control this behavior.\n",
      "  _warn_prf(average, modifier, msg_start, len(result))\n",
      "/home/pruthvish/JRF/RoadNetwork/RoadNetwork_VirtualEnv/lib/python3.8/site-packages/sklearn/metrics/_classification.py:1599: UndefinedMetricWarning: F-score is ill-defined and being set to 0.0 in labels with no true nor predicted samples. Use `zero_division` parameter to control this behavior.\n",
      "  _warn_prf(average, \"true nor predicted\", \"F-score is\", len(true_sum))\n",
      "/home/pruthvish/JRF/RoadNetwork/RoadNetwork_VirtualEnv/lib/python3.8/site-packages/sklearn/metrics/_classification.py:1334: UndefinedMetricWarning: Precision is ill-defined and being set to 0.0 in labels with no predicted samples. Use `zero_division` parameter to control this behavior.\n",
      "  _warn_prf(average, modifier, msg_start, len(result))\n",
      "/home/pruthvish/JRF/RoadNetwork/RoadNetwork_VirtualEnv/lib/python3.8/site-packages/sklearn/metrics/_classification.py:1334: UndefinedMetricWarning: Recall is ill-defined and being set to 0.0 in labels with no true samples. Use `zero_division` parameter to control this behavior.\n",
      "  _warn_prf(average, modifier, msg_start, len(result))\n",
      "/home/pruthvish/JRF/RoadNetwork/RoadNetwork_VirtualEnv/lib/python3.8/site-packages/sklearn/metrics/_classification.py:1599: UndefinedMetricWarning: F-score is ill-defined and being set to 0.0 in labels with no true nor predicted samples. Use `zero_division` parameter to control this behavior.\n",
      "  _warn_prf(average, \"true nor predicted\", \"F-score is\", len(true_sum))\n",
      "/home/pruthvish/JRF/RoadNetwork/RoadNetwork_VirtualEnv/lib/python3.8/site-packages/sklearn/metrics/_classification.py:1334: UndefinedMetricWarning: Precision is ill-defined and being set to 0.0 in labels with no predicted samples. Use `zero_division` parameter to control this behavior.\n",
      "  _warn_prf(average, modifier, msg_start, len(result))\n",
      "/home/pruthvish/JRF/RoadNetwork/RoadNetwork_VirtualEnv/lib/python3.8/site-packages/sklearn/metrics/_classification.py:1334: UndefinedMetricWarning: Recall is ill-defined and being set to 0.0 in labels with no true samples. Use `zero_division` parameter to control this behavior.\n",
      "  _warn_prf(average, modifier, msg_start, len(result))\n",
      "/home/pruthvish/JRF/RoadNetwork/RoadNetwork_VirtualEnv/lib/python3.8/site-packages/sklearn/metrics/_classification.py:1599: UndefinedMetricWarning: F-score is ill-defined and being set to 0.0 in labels with no true nor predicted samples. Use `zero_division` parameter to control this behavior.\n",
      "  _warn_prf(average, \"true nor predicted\", \"F-score is\", len(true_sum))\n",
      "/home/pruthvish/JRF/RoadNetwork/RoadNetwork_VirtualEnv/lib/python3.8/site-packages/sklearn/metrics/_classification.py:1334: UndefinedMetricWarning: Precision is ill-defined and being set to 0.0 in labels with no predicted samples. Use `zero_division` parameter to control this behavior.\n",
      "  _warn_prf(average, modifier, msg_start, len(result))\n",
      "/home/pruthvish/JRF/RoadNetwork/RoadNetwork_VirtualEnv/lib/python3.8/site-packages/sklearn/metrics/_classification.py:1334: UndefinedMetricWarning: Recall is ill-defined and being set to 0.0 in labels with no true samples. Use `zero_division` parameter to control this behavior.\n",
      "  _warn_prf(average, modifier, msg_start, len(result))\n",
      "/home/pruthvish/JRF/RoadNetwork/RoadNetwork_VirtualEnv/lib/python3.8/site-packages/sklearn/metrics/_classification.py:1599: UndefinedMetricWarning: F-score is ill-defined and being set to 0.0 in labels with no true nor predicted samples. Use `zero_division` parameter to control this behavior.\n",
      "  _warn_prf(average, \"true nor predicted\", \"F-score is\", len(true_sum))\n",
      "/home/pruthvish/JRF/RoadNetwork/RoadNetwork_VirtualEnv/lib/python3.8/site-packages/sklearn/metrics/_classification.py:1334: UndefinedMetricWarning: Precision is ill-defined and being set to 0.0 in labels with no predicted samples. Use `zero_division` parameter to control this behavior.\n",
      "  _warn_prf(average, modifier, msg_start, len(result))\n",
      "/home/pruthvish/JRF/RoadNetwork/RoadNetwork_VirtualEnv/lib/python3.8/site-packages/sklearn/metrics/_classification.py:1334: UndefinedMetricWarning: Recall is ill-defined and being set to 0.0 in labels with no true samples. Use `zero_division` parameter to control this behavior.\n",
      "  _warn_prf(average, modifier, msg_start, len(result))\n",
      "/home/pruthvish/JRF/RoadNetwork/RoadNetwork_VirtualEnv/lib/python3.8/site-packages/sklearn/metrics/_classification.py:1599: UndefinedMetricWarning: F-score is ill-defined and being set to 0.0 in labels with no true nor predicted samples. Use `zero_division` parameter to control this behavior.\n",
      "  _warn_prf(average, \"true nor predicted\", \"F-score is\", len(true_sum))\n",
      "/home/pruthvish/JRF/RoadNetwork/RoadNetwork_VirtualEnv/lib/python3.8/site-packages/sklearn/metrics/_classification.py:1334: UndefinedMetricWarning: Precision is ill-defined and being set to 0.0 in labels with no predicted samples. Use `zero_division` parameter to control this behavior.\n",
      "  _warn_prf(average, modifier, msg_start, len(result))\n",
      "/home/pruthvish/JRF/RoadNetwork/RoadNetwork_VirtualEnv/lib/python3.8/site-packages/sklearn/metrics/_classification.py:1334: UndefinedMetricWarning: Recall is ill-defined and being set to 0.0 in labels with no true samples. Use `zero_division` parameter to control this behavior.\n",
      "  _warn_prf(average, modifier, msg_start, len(result))\n",
      "/home/pruthvish/JRF/RoadNetwork/RoadNetwork_VirtualEnv/lib/python3.8/site-packages/sklearn/metrics/_classification.py:1599: UndefinedMetricWarning: F-score is ill-defined and being set to 0.0 in labels with no true nor predicted samples. Use `zero_division` parameter to control this behavior.\n",
      "  _warn_prf(average, \"true nor predicted\", \"F-score is\", len(true_sum))\n",
      "/home/pruthvish/JRF/RoadNetwork/RoadNetwork_VirtualEnv/lib/python3.8/site-packages/sklearn/metrics/_classification.py:1334: UndefinedMetricWarning: Precision is ill-defined and being set to 0.0 in labels with no predicted samples. Use `zero_division` parameter to control this behavior.\n",
      "  _warn_prf(average, modifier, msg_start, len(result))\n",
      "/home/pruthvish/JRF/RoadNetwork/RoadNetwork_VirtualEnv/lib/python3.8/site-packages/sklearn/metrics/_classification.py:1334: UndefinedMetricWarning: Recall is ill-defined and being set to 0.0 in labels with no true samples. Use `zero_division` parameter to control this behavior.\n",
      "  _warn_prf(average, modifier, msg_start, len(result))\n",
      "/home/pruthvish/JRF/RoadNetwork/RoadNetwork_VirtualEnv/lib/python3.8/site-packages/sklearn/metrics/_classification.py:1599: UndefinedMetricWarning: F-score is ill-defined and being set to 0.0 in labels with no true nor predicted samples. Use `zero_division` parameter to control this behavior.\n",
      "  _warn_prf(average, \"true nor predicted\", \"F-score is\", len(true_sum))\n",
      "/home/pruthvish/JRF/RoadNetwork/RoadNetwork_VirtualEnv/lib/python3.8/site-packages/sklearn/metrics/_classification.py:1334: UndefinedMetricWarning: Precision is ill-defined and being set to 0.0 in labels with no predicted samples. Use `zero_division` parameter to control this behavior.\n",
      "  _warn_prf(average, modifier, msg_start, len(result))\n",
      "/home/pruthvish/JRF/RoadNetwork/RoadNetwork_VirtualEnv/lib/python3.8/site-packages/sklearn/metrics/_classification.py:1334: UndefinedMetricWarning: Recall is ill-defined and being set to 0.0 in labels with no true samples. Use `zero_division` parameter to control this behavior.\n",
      "  _warn_prf(average, modifier, msg_start, len(result))\n",
      "/home/pruthvish/JRF/RoadNetwork/RoadNetwork_VirtualEnv/lib/python3.8/site-packages/sklearn/metrics/_classification.py:1599: UndefinedMetricWarning: F-score is ill-defined and being set to 0.0 in labels with no true nor predicted samples. Use `zero_division` parameter to control this behavior.\n",
      "  _warn_prf(average, \"true nor predicted\", \"F-score is\", len(true_sum))\n",
      "/home/pruthvish/JRF/RoadNetwork/RoadNetwork_VirtualEnv/lib/python3.8/site-packages/sklearn/metrics/_classification.py:1334: UndefinedMetricWarning: Precision is ill-defined and being set to 0.0 in labels with no predicted samples. Use `zero_division` parameter to control this behavior.\n",
      "  _warn_prf(average, modifier, msg_start, len(result))\n",
      "/home/pruthvish/JRF/RoadNetwork/RoadNetwork_VirtualEnv/lib/python3.8/site-packages/sklearn/metrics/_classification.py:1334: UndefinedMetricWarning: Recall is ill-defined and being set to 0.0 in labels with no true samples. Use `zero_division` parameter to control this behavior.\n",
      "  _warn_prf(average, modifier, msg_start, len(result))\n",
      "/home/pruthvish/JRF/RoadNetwork/RoadNetwork_VirtualEnv/lib/python3.8/site-packages/sklearn/metrics/_classification.py:1599: UndefinedMetricWarning: F-score is ill-defined and being set to 0.0 in labels with no true nor predicted samples. Use `zero_division` parameter to control this behavior.\n",
      "  _warn_prf(average, \"true nor predicted\", \"F-score is\", len(true_sum))\n"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "Feature set-4\n",
      "Classifier, ClassifierName LogisticRegression(random_state=0) LogisticRegression\n",
      "Feature set-1\n"
     ]
    },
    {
     "name": "stderr",
     "output_type": "stream",
     "text": [
      "/home/pruthvish/JRF/RoadNetwork/RoadNetwork_VirtualEnv/lib/python3.8/site-packages/sklearn/metrics/_classification.py:1334: UndefinedMetricWarning: Precision is ill-defined and being set to 0.0 in labels with no predicted samples. Use `zero_division` parameter to control this behavior.\n",
      "  _warn_prf(average, modifier, msg_start, len(result))\n",
      "/home/pruthvish/JRF/RoadNetwork/RoadNetwork_VirtualEnv/lib/python3.8/site-packages/sklearn/metrics/_classification.py:1334: UndefinedMetricWarning: Recall is ill-defined and being set to 0.0 in labels with no true samples. Use `zero_division` parameter to control this behavior.\n",
      "  _warn_prf(average, modifier, msg_start, len(result))\n",
      "/home/pruthvish/JRF/RoadNetwork/RoadNetwork_VirtualEnv/lib/python3.8/site-packages/sklearn/metrics/_classification.py:1599: UndefinedMetricWarning: F-score is ill-defined and being set to 0.0 in labels with no true nor predicted samples. Use `zero_division` parameter to control this behavior.\n",
      "  _warn_prf(average, \"true nor predicted\", \"F-score is\", len(true_sum))\n",
      "/home/pruthvish/JRF/RoadNetwork/RoadNetwork_VirtualEnv/lib/python3.8/site-packages/sklearn/metrics/_classification.py:1334: UndefinedMetricWarning: Precision is ill-defined and being set to 0.0 in labels with no predicted samples. Use `zero_division` parameter to control this behavior.\n",
      "  _warn_prf(average, modifier, msg_start, len(result))\n",
      "/home/pruthvish/JRF/RoadNetwork/RoadNetwork_VirtualEnv/lib/python3.8/site-packages/sklearn/metrics/_classification.py:1334: UndefinedMetricWarning: Recall is ill-defined and being set to 0.0 in labels with no true samples. Use `zero_division` parameter to control this behavior.\n",
      "  _warn_prf(average, modifier, msg_start, len(result))\n",
      "/home/pruthvish/JRF/RoadNetwork/RoadNetwork_VirtualEnv/lib/python3.8/site-packages/sklearn/metrics/_classification.py:1599: UndefinedMetricWarning: F-score is ill-defined and being set to 0.0 in labels with no true nor predicted samples. Use `zero_division` parameter to control this behavior.\n",
      "  _warn_prf(average, \"true nor predicted\", \"F-score is\", len(true_sum))\n",
      "/home/pruthvish/JRF/RoadNetwork/RoadNetwork_VirtualEnv/lib/python3.8/site-packages/sklearn/metrics/_classification.py:1334: UndefinedMetricWarning: Precision is ill-defined and being set to 0.0 in labels with no predicted samples. Use `zero_division` parameter to control this behavior.\n",
      "  _warn_prf(average, modifier, msg_start, len(result))\n",
      "/home/pruthvish/JRF/RoadNetwork/RoadNetwork_VirtualEnv/lib/python3.8/site-packages/sklearn/metrics/_classification.py:1334: UndefinedMetricWarning: Recall is ill-defined and being set to 0.0 in labels with no true samples. Use `zero_division` parameter to control this behavior.\n",
      "  _warn_prf(average, modifier, msg_start, len(result))\n",
      "/home/pruthvish/JRF/RoadNetwork/RoadNetwork_VirtualEnv/lib/python3.8/site-packages/sklearn/metrics/_classification.py:1599: UndefinedMetricWarning: F-score is ill-defined and being set to 0.0 in labels with no true nor predicted samples. Use `zero_division` parameter to control this behavior.\n",
      "  _warn_prf(average, \"true nor predicted\", \"F-score is\", len(true_sum))\n",
      "/home/pruthvish/JRF/RoadNetwork/RoadNetwork_VirtualEnv/lib/python3.8/site-packages/sklearn/metrics/_classification.py:1334: UndefinedMetricWarning: Precision is ill-defined and being set to 0.0 in labels with no predicted samples. Use `zero_division` parameter to control this behavior.\n",
      "  _warn_prf(average, modifier, msg_start, len(result))\n",
      "/home/pruthvish/JRF/RoadNetwork/RoadNetwork_VirtualEnv/lib/python3.8/site-packages/sklearn/metrics/_classification.py:1334: UndefinedMetricWarning: Recall is ill-defined and being set to 0.0 in labels with no true samples. Use `zero_division` parameter to control this behavior.\n",
      "  _warn_prf(average, modifier, msg_start, len(result))\n",
      "/home/pruthvish/JRF/RoadNetwork/RoadNetwork_VirtualEnv/lib/python3.8/site-packages/sklearn/metrics/_classification.py:1599: UndefinedMetricWarning: F-score is ill-defined and being set to 0.0 in labels with no true nor predicted samples. Use `zero_division` parameter to control this behavior.\n",
      "  _warn_prf(average, \"true nor predicted\", \"F-score is\", len(true_sum))\n",
      "/home/pruthvish/JRF/RoadNetwork/RoadNetwork_VirtualEnv/lib/python3.8/site-packages/sklearn/metrics/_classification.py:1334: UndefinedMetricWarning: Precision is ill-defined and being set to 0.0 in labels with no predicted samples. Use `zero_division` parameter to control this behavior.\n",
      "  _warn_prf(average, modifier, msg_start, len(result))\n",
      "/home/pruthvish/JRF/RoadNetwork/RoadNetwork_VirtualEnv/lib/python3.8/site-packages/sklearn/metrics/_classification.py:1334: UndefinedMetricWarning: Recall is ill-defined and being set to 0.0 in labels with no true samples. Use `zero_division` parameter to control this behavior.\n",
      "  _warn_prf(average, modifier, msg_start, len(result))\n",
      "/home/pruthvish/JRF/RoadNetwork/RoadNetwork_VirtualEnv/lib/python3.8/site-packages/sklearn/metrics/_classification.py:1599: UndefinedMetricWarning: F-score is ill-defined and being set to 0.0 in labels with no true nor predicted samples. Use `zero_division` parameter to control this behavior.\n",
      "  _warn_prf(average, \"true nor predicted\", \"F-score is\", len(true_sum))\n",
      "/home/pruthvish/JRF/RoadNetwork/RoadNetwork_VirtualEnv/lib/python3.8/site-packages/sklearn/metrics/_classification.py:1334: UndefinedMetricWarning: Precision is ill-defined and being set to 0.0 in labels with no predicted samples. Use `zero_division` parameter to control this behavior.\n",
      "  _warn_prf(average, modifier, msg_start, len(result))\n",
      "/home/pruthvish/JRF/RoadNetwork/RoadNetwork_VirtualEnv/lib/python3.8/site-packages/sklearn/metrics/_classification.py:1334: UndefinedMetricWarning: Recall is ill-defined and being set to 0.0 in labels with no true samples. Use `zero_division` parameter to control this behavior.\n",
      "  _warn_prf(average, modifier, msg_start, len(result))\n",
      "/home/pruthvish/JRF/RoadNetwork/RoadNetwork_VirtualEnv/lib/python3.8/site-packages/sklearn/metrics/_classification.py:1599: UndefinedMetricWarning: F-score is ill-defined and being set to 0.0 in labels with no true nor predicted samples. Use `zero_division` parameter to control this behavior.\n",
      "  _warn_prf(average, \"true nor predicted\", \"F-score is\", len(true_sum))\n",
      "/home/pruthvish/JRF/RoadNetwork/RoadNetwork_VirtualEnv/lib/python3.8/site-packages/sklearn/metrics/_classification.py:1334: UndefinedMetricWarning: Precision is ill-defined and being set to 0.0 in labels with no predicted samples. Use `zero_division` parameter to control this behavior.\n",
      "  _warn_prf(average, modifier, msg_start, len(result))\n",
      "/home/pruthvish/JRF/RoadNetwork/RoadNetwork_VirtualEnv/lib/python3.8/site-packages/sklearn/metrics/_classification.py:1334: UndefinedMetricWarning: Recall is ill-defined and being set to 0.0 in labels with no true samples. Use `zero_division` parameter to control this behavior.\n",
      "  _warn_prf(average, modifier, msg_start, len(result))\n",
      "/home/pruthvish/JRF/RoadNetwork/RoadNetwork_VirtualEnv/lib/python3.8/site-packages/sklearn/metrics/_classification.py:1599: UndefinedMetricWarning: F-score is ill-defined and being set to 0.0 in labels with no true nor predicted samples. Use `zero_division` parameter to control this behavior.\n",
      "  _warn_prf(average, \"true nor predicted\", \"F-score is\", len(true_sum))\n",
      "/home/pruthvish/JRF/RoadNetwork/RoadNetwork_VirtualEnv/lib/python3.8/site-packages/sklearn/metrics/_classification.py:1334: UndefinedMetricWarning: Precision is ill-defined and being set to 0.0 in labels with no predicted samples. Use `zero_division` parameter to control this behavior.\n",
      "  _warn_prf(average, modifier, msg_start, len(result))\n",
      "/home/pruthvish/JRF/RoadNetwork/RoadNetwork_VirtualEnv/lib/python3.8/site-packages/sklearn/metrics/_classification.py:1334: UndefinedMetricWarning: Recall is ill-defined and being set to 0.0 in labels with no true samples. Use `zero_division` parameter to control this behavior.\n",
      "  _warn_prf(average, modifier, msg_start, len(result))\n",
      "/home/pruthvish/JRF/RoadNetwork/RoadNetwork_VirtualEnv/lib/python3.8/site-packages/sklearn/metrics/_classification.py:1599: UndefinedMetricWarning: F-score is ill-defined and being set to 0.0 in labels with no true nor predicted samples. Use `zero_division` parameter to control this behavior.\n",
      "  _warn_prf(average, \"true nor predicted\", \"F-score is\", len(true_sum))\n",
      "/home/pruthvish/JRF/RoadNetwork/RoadNetwork_VirtualEnv/lib/python3.8/site-packages/sklearn/metrics/_classification.py:1334: UndefinedMetricWarning: Precision is ill-defined and being set to 0.0 in labels with no predicted samples. Use `zero_division` parameter to control this behavior.\n",
      "  _warn_prf(average, modifier, msg_start, len(result))\n",
      "/home/pruthvish/JRF/RoadNetwork/RoadNetwork_VirtualEnv/lib/python3.8/site-packages/sklearn/metrics/_classification.py:1334: UndefinedMetricWarning: Recall is ill-defined and being set to 0.0 in labels with no true samples. Use `zero_division` parameter to control this behavior.\n",
      "  _warn_prf(average, modifier, msg_start, len(result))\n",
      "/home/pruthvish/JRF/RoadNetwork/RoadNetwork_VirtualEnv/lib/python3.8/site-packages/sklearn/metrics/_classification.py:1599: UndefinedMetricWarning: F-score is ill-defined and being set to 0.0 in labels with no true nor predicted samples. Use `zero_division` parameter to control this behavior.\n",
      "  _warn_prf(average, \"true nor predicted\", \"F-score is\", len(true_sum))\n",
      "/home/pruthvish/JRF/RoadNetwork/RoadNetwork_VirtualEnv/lib/python3.8/site-packages/sklearn/metrics/_classification.py:1334: UndefinedMetricWarning: Precision is ill-defined and being set to 0.0 in labels with no predicted samples. Use `zero_division` parameter to control this behavior.\n",
      "  _warn_prf(average, modifier, msg_start, len(result))\n",
      "/home/pruthvish/JRF/RoadNetwork/RoadNetwork_VirtualEnv/lib/python3.8/site-packages/sklearn/metrics/_classification.py:1334: UndefinedMetricWarning: Recall is ill-defined and being set to 0.0 in labels with no true samples. Use `zero_division` parameter to control this behavior.\n",
      "  _warn_prf(average, modifier, msg_start, len(result))\n",
      "/home/pruthvish/JRF/RoadNetwork/RoadNetwork_VirtualEnv/lib/python3.8/site-packages/sklearn/metrics/_classification.py:1599: UndefinedMetricWarning: F-score is ill-defined and being set to 0.0 in labels with no true nor predicted samples. Use `zero_division` parameter to control this behavior.\n",
      "  _warn_prf(average, \"true nor predicted\", \"F-score is\", len(true_sum))\n"
     ]
    },
    {
     "name": "stderr",
     "output_type": "stream",
     "text": [
      "/home/pruthvish/JRF/RoadNetwork/RoadNetwork_VirtualEnv/lib/python3.8/site-packages/sklearn/linear_model/_logistic.py:444: ConvergenceWarning: lbfgs failed to converge (status=1):\n",
      "STOP: TOTAL NO. of ITERATIONS REACHED LIMIT.\n",
      "\n",
      "Increase the number of iterations (max_iter) or scale the data as shown in:\n",
      "    https://scikit-learn.org/stable/modules/preprocessing.html\n",
      "Please also refer to the documentation for alternative solver options:\n",
      "    https://scikit-learn.org/stable/modules/linear_model.html#logistic-regression\n",
      "  n_iter_i = _check_optimize_result(\n",
      "/home/pruthvish/JRF/RoadNetwork/RoadNetwork_VirtualEnv/lib/python3.8/site-packages/sklearn/metrics/_classification.py:1334: UndefinedMetricWarning: Precision is ill-defined and being set to 0.0 in labels with no predicted samples. Use `zero_division` parameter to control this behavior.\n",
      "  _warn_prf(average, modifier, msg_start, len(result))\n",
      "/home/pruthvish/JRF/RoadNetwork/RoadNetwork_VirtualEnv/lib/python3.8/site-packages/sklearn/metrics/_classification.py:1334: UndefinedMetricWarning: Recall is ill-defined and being set to 0.0 in labels with no true samples. Use `zero_division` parameter to control this behavior.\n",
      "  _warn_prf(average, modifier, msg_start, len(result))\n",
      "/home/pruthvish/JRF/RoadNetwork/RoadNetwork_VirtualEnv/lib/python3.8/site-packages/sklearn/metrics/_classification.py:1599: UndefinedMetricWarning: F-score is ill-defined and being set to 0.0 in labels with no true nor predicted samples. Use `zero_division` parameter to control this behavior.\n",
      "  _warn_prf(average, \"true nor predicted\", \"F-score is\", len(true_sum))\n",
      "/home/pruthvish/JRF/RoadNetwork/RoadNetwork_VirtualEnv/lib/python3.8/site-packages/sklearn/linear_model/_logistic.py:444: ConvergenceWarning: lbfgs failed to converge (status=1):\n",
      "STOP: TOTAL NO. of ITERATIONS REACHED LIMIT.\n",
      "\n",
      "Increase the number of iterations (max_iter) or scale the data as shown in:\n",
      "    https://scikit-learn.org/stable/modules/preprocessing.html\n",
      "Please also refer to the documentation for alternative solver options:\n",
      "    https://scikit-learn.org/stable/modules/linear_model.html#logistic-regression\n",
      "  n_iter_i = _check_optimize_result(\n",
      "/home/pruthvish/JRF/RoadNetwork/RoadNetwork_VirtualEnv/lib/python3.8/site-packages/sklearn/metrics/_classification.py:1334: UndefinedMetricWarning: Precision is ill-defined and being set to 0.0 in labels with no predicted samples. Use `zero_division` parameter to control this behavior.\n",
      "  _warn_prf(average, modifier, msg_start, len(result))\n",
      "/home/pruthvish/JRF/RoadNetwork/RoadNetwork_VirtualEnv/lib/python3.8/site-packages/sklearn/metrics/_classification.py:1334: UndefinedMetricWarning: Recall is ill-defined and being set to 0.0 in labels with no true samples. Use `zero_division` parameter to control this behavior.\n",
      "  _warn_prf(average, modifier, msg_start, len(result))\n",
      "/home/pruthvish/JRF/RoadNetwork/RoadNetwork_VirtualEnv/lib/python3.8/site-packages/sklearn/metrics/_classification.py:1599: UndefinedMetricWarning: F-score is ill-defined and being set to 0.0 in labels with no true nor predicted samples. Use `zero_division` parameter to control this behavior.\n",
      "  _warn_prf(average, \"true nor predicted\", \"F-score is\", len(true_sum))\n",
      "/home/pruthvish/JRF/RoadNetwork/RoadNetwork_VirtualEnv/lib/python3.8/site-packages/sklearn/linear_model/_logistic.py:444: ConvergenceWarning: lbfgs failed to converge (status=1):\n",
      "STOP: TOTAL NO. of ITERATIONS REACHED LIMIT.\n",
      "\n",
      "Increase the number of iterations (max_iter) or scale the data as shown in:\n",
      "    https://scikit-learn.org/stable/modules/preprocessing.html\n",
      "Please also refer to the documentation for alternative solver options:\n",
      "    https://scikit-learn.org/stable/modules/linear_model.html#logistic-regression\n",
      "  n_iter_i = _check_optimize_result(\n",
      "/home/pruthvish/JRF/RoadNetwork/RoadNetwork_VirtualEnv/lib/python3.8/site-packages/sklearn/metrics/_classification.py:1334: UndefinedMetricWarning: Precision is ill-defined and being set to 0.0 in labels with no predicted samples. Use `zero_division` parameter to control this behavior.\n",
      "  _warn_prf(average, modifier, msg_start, len(result))\n",
      "/home/pruthvish/JRF/RoadNetwork/RoadNetwork_VirtualEnv/lib/python3.8/site-packages/sklearn/metrics/_classification.py:1334: UndefinedMetricWarning: Recall is ill-defined and being set to 0.0 in labels with no true samples. Use `zero_division` parameter to control this behavior.\n",
      "  _warn_prf(average, modifier, msg_start, len(result))\n",
      "/home/pruthvish/JRF/RoadNetwork/RoadNetwork_VirtualEnv/lib/python3.8/site-packages/sklearn/metrics/_classification.py:1599: UndefinedMetricWarning: F-score is ill-defined and being set to 0.0 in labels with no true nor predicted samples. Use `zero_division` parameter to control this behavior.\n",
      "  _warn_prf(average, \"true nor predicted\", \"F-score is\", len(true_sum))\n",
      "/home/pruthvish/JRF/RoadNetwork/RoadNetwork_VirtualEnv/lib/python3.8/site-packages/sklearn/linear_model/_logistic.py:444: ConvergenceWarning: lbfgs failed to converge (status=1):\n",
      "STOP: TOTAL NO. of ITERATIONS REACHED LIMIT.\n",
      "\n",
      "Increase the number of iterations (max_iter) or scale the data as shown in:\n",
      "    https://scikit-learn.org/stable/modules/preprocessing.html\n",
      "Please also refer to the documentation for alternative solver options:\n",
      "    https://scikit-learn.org/stable/modules/linear_model.html#logistic-regression\n",
      "  n_iter_i = _check_optimize_result(\n",
      "/home/pruthvish/JRF/RoadNetwork/RoadNetwork_VirtualEnv/lib/python3.8/site-packages/sklearn/metrics/_classification.py:1334: UndefinedMetricWarning: Precision is ill-defined and being set to 0.0 in labels with no predicted samples. Use `zero_division` parameter to control this behavior.\n",
      "  _warn_prf(average, modifier, msg_start, len(result))\n",
      "/home/pruthvish/JRF/RoadNetwork/RoadNetwork_VirtualEnv/lib/python3.8/site-packages/sklearn/metrics/_classification.py:1334: UndefinedMetricWarning: Recall is ill-defined and being set to 0.0 in labels with no true samples. Use `zero_division` parameter to control this behavior.\n",
      "  _warn_prf(average, modifier, msg_start, len(result))\n",
      "/home/pruthvish/JRF/RoadNetwork/RoadNetwork_VirtualEnv/lib/python3.8/site-packages/sklearn/metrics/_classification.py:1599: UndefinedMetricWarning: F-score is ill-defined and being set to 0.0 in labels with no true nor predicted samples. Use `zero_division` parameter to control this behavior.\n",
      "  _warn_prf(average, \"true nor predicted\", \"F-score is\", len(true_sum))\n",
      "/home/pruthvish/JRF/RoadNetwork/RoadNetwork_VirtualEnv/lib/python3.8/site-packages/sklearn/linear_model/_logistic.py:444: ConvergenceWarning: lbfgs failed to converge (status=1):\n",
      "STOP: TOTAL NO. of ITERATIONS REACHED LIMIT.\n",
      "\n",
      "Increase the number of iterations (max_iter) or scale the data as shown in:\n",
      "    https://scikit-learn.org/stable/modules/preprocessing.html\n",
      "Please also refer to the documentation for alternative solver options:\n",
      "    https://scikit-learn.org/stable/modules/linear_model.html#logistic-regression\n",
      "  n_iter_i = _check_optimize_result(\n",
      "/home/pruthvish/JRF/RoadNetwork/RoadNetwork_VirtualEnv/lib/python3.8/site-packages/sklearn/metrics/_classification.py:1334: UndefinedMetricWarning: Precision is ill-defined and being set to 0.0 in labels with no predicted samples. Use `zero_division` parameter to control this behavior.\n",
      "  _warn_prf(average, modifier, msg_start, len(result))\n",
      "/home/pruthvish/JRF/RoadNetwork/RoadNetwork_VirtualEnv/lib/python3.8/site-packages/sklearn/metrics/_classification.py:1334: UndefinedMetricWarning: Recall is ill-defined and being set to 0.0 in labels with no true samples. Use `zero_division` parameter to control this behavior.\n",
      "  _warn_prf(average, modifier, msg_start, len(result))\n",
      "/home/pruthvish/JRF/RoadNetwork/RoadNetwork_VirtualEnv/lib/python3.8/site-packages/sklearn/metrics/_classification.py:1599: UndefinedMetricWarning: F-score is ill-defined and being set to 0.0 in labels with no true nor predicted samples. Use `zero_division` parameter to control this behavior.\n",
      "  _warn_prf(average, \"true nor predicted\", \"F-score is\", len(true_sum))\n",
      "/home/pruthvish/JRF/RoadNetwork/RoadNetwork_VirtualEnv/lib/python3.8/site-packages/sklearn/linear_model/_logistic.py:444: ConvergenceWarning: lbfgs failed to converge (status=1):\n",
      "STOP: TOTAL NO. of ITERATIONS REACHED LIMIT.\n",
      "\n",
      "Increase the number of iterations (max_iter) or scale the data as shown in:\n",
      "    https://scikit-learn.org/stable/modules/preprocessing.html\n",
      "Please also refer to the documentation for alternative solver options:\n",
      "    https://scikit-learn.org/stable/modules/linear_model.html#logistic-regression\n",
      "  n_iter_i = _check_optimize_result(\n",
      "/home/pruthvish/JRF/RoadNetwork/RoadNetwork_VirtualEnv/lib/python3.8/site-packages/sklearn/metrics/_classification.py:1334: UndefinedMetricWarning: Precision is ill-defined and being set to 0.0 in labels with no predicted samples. Use `zero_division` parameter to control this behavior.\n",
      "  _warn_prf(average, modifier, msg_start, len(result))\n",
      "/home/pruthvish/JRF/RoadNetwork/RoadNetwork_VirtualEnv/lib/python3.8/site-packages/sklearn/metrics/_classification.py:1334: UndefinedMetricWarning: Recall is ill-defined and being set to 0.0 in labels with no true samples. Use `zero_division` parameter to control this behavior.\n",
      "  _warn_prf(average, modifier, msg_start, len(result))\n",
      "/home/pruthvish/JRF/RoadNetwork/RoadNetwork_VirtualEnv/lib/python3.8/site-packages/sklearn/metrics/_classification.py:1599: UndefinedMetricWarning: F-score is ill-defined and being set to 0.0 in labels with no true nor predicted samples. Use `zero_division` parameter to control this behavior.\n",
      "  _warn_prf(average, \"true nor predicted\", \"F-score is\", len(true_sum))\n"
     ]
    },
    {
     "name": "stderr",
     "output_type": "stream",
     "text": [
      "/home/pruthvish/JRF/RoadNetwork/RoadNetwork_VirtualEnv/lib/python3.8/site-packages/sklearn/linear_model/_logistic.py:444: ConvergenceWarning: lbfgs failed to converge (status=1):\n",
      "STOP: TOTAL NO. of ITERATIONS REACHED LIMIT.\n",
      "\n",
      "Increase the number of iterations (max_iter) or scale the data as shown in:\n",
      "    https://scikit-learn.org/stable/modules/preprocessing.html\n",
      "Please also refer to the documentation for alternative solver options:\n",
      "    https://scikit-learn.org/stable/modules/linear_model.html#logistic-regression\n",
      "  n_iter_i = _check_optimize_result(\n",
      "/home/pruthvish/JRF/RoadNetwork/RoadNetwork_VirtualEnv/lib/python3.8/site-packages/sklearn/metrics/_classification.py:1334: UndefinedMetricWarning: Precision is ill-defined and being set to 0.0 in labels with no predicted samples. Use `zero_division` parameter to control this behavior.\n",
      "  _warn_prf(average, modifier, msg_start, len(result))\n",
      "/home/pruthvish/JRF/RoadNetwork/RoadNetwork_VirtualEnv/lib/python3.8/site-packages/sklearn/metrics/_classification.py:1334: UndefinedMetricWarning: Recall is ill-defined and being set to 0.0 in labels with no true samples. Use `zero_division` parameter to control this behavior.\n",
      "  _warn_prf(average, modifier, msg_start, len(result))\n",
      "/home/pruthvish/JRF/RoadNetwork/RoadNetwork_VirtualEnv/lib/python3.8/site-packages/sklearn/metrics/_classification.py:1599: UndefinedMetricWarning: F-score is ill-defined and being set to 0.0 in labels with no true nor predicted samples. Use `zero_division` parameter to control this behavior.\n",
      "  _warn_prf(average, \"true nor predicted\", \"F-score is\", len(true_sum))\n",
      "/home/pruthvish/JRF/RoadNetwork/RoadNetwork_VirtualEnv/lib/python3.8/site-packages/sklearn/linear_model/_logistic.py:444: ConvergenceWarning: lbfgs failed to converge (status=1):\n",
      "STOP: TOTAL NO. of ITERATIONS REACHED LIMIT.\n",
      "\n",
      "Increase the number of iterations (max_iter) or scale the data as shown in:\n",
      "    https://scikit-learn.org/stable/modules/preprocessing.html\n",
      "Please also refer to the documentation for alternative solver options:\n",
      "    https://scikit-learn.org/stable/modules/linear_model.html#logistic-regression\n",
      "  n_iter_i = _check_optimize_result(\n",
      "/home/pruthvish/JRF/RoadNetwork/RoadNetwork_VirtualEnv/lib/python3.8/site-packages/sklearn/metrics/_classification.py:1334: UndefinedMetricWarning: Precision is ill-defined and being set to 0.0 in labels with no predicted samples. Use `zero_division` parameter to control this behavior.\n",
      "  _warn_prf(average, modifier, msg_start, len(result))\n",
      "/home/pruthvish/JRF/RoadNetwork/RoadNetwork_VirtualEnv/lib/python3.8/site-packages/sklearn/metrics/_classification.py:1334: UndefinedMetricWarning: Recall is ill-defined and being set to 0.0 in labels with no true samples. Use `zero_division` parameter to control this behavior.\n",
      "  _warn_prf(average, modifier, msg_start, len(result))\n",
      "/home/pruthvish/JRF/RoadNetwork/RoadNetwork_VirtualEnv/lib/python3.8/site-packages/sklearn/metrics/_classification.py:1599: UndefinedMetricWarning: F-score is ill-defined and being set to 0.0 in labels with no true nor predicted samples. Use `zero_division` parameter to control this behavior.\n",
      "  _warn_prf(average, \"true nor predicted\", \"F-score is\", len(true_sum))\n",
      "/home/pruthvish/JRF/RoadNetwork/RoadNetwork_VirtualEnv/lib/python3.8/site-packages/sklearn/linear_model/_logistic.py:444: ConvergenceWarning: lbfgs failed to converge (status=1):\n",
      "STOP: TOTAL NO. of ITERATIONS REACHED LIMIT.\n",
      "\n",
      "Increase the number of iterations (max_iter) or scale the data as shown in:\n",
      "    https://scikit-learn.org/stable/modules/preprocessing.html\n",
      "Please also refer to the documentation for alternative solver options:\n",
      "    https://scikit-learn.org/stable/modules/linear_model.html#logistic-regression\n",
      "  n_iter_i = _check_optimize_result(\n",
      "/home/pruthvish/JRF/RoadNetwork/RoadNetwork_VirtualEnv/lib/python3.8/site-packages/sklearn/metrics/_classification.py:1334: UndefinedMetricWarning: Precision is ill-defined and being set to 0.0 in labels with no predicted samples. Use `zero_division` parameter to control this behavior.\n",
      "  _warn_prf(average, modifier, msg_start, len(result))\n",
      "/home/pruthvish/JRF/RoadNetwork/RoadNetwork_VirtualEnv/lib/python3.8/site-packages/sklearn/metrics/_classification.py:1334: UndefinedMetricWarning: Recall is ill-defined and being set to 0.0 in labels with no true samples. Use `zero_division` parameter to control this behavior.\n",
      "  _warn_prf(average, modifier, msg_start, len(result))\n",
      "/home/pruthvish/JRF/RoadNetwork/RoadNetwork_VirtualEnv/lib/python3.8/site-packages/sklearn/metrics/_classification.py:1599: UndefinedMetricWarning: F-score is ill-defined and being set to 0.0 in labels with no true nor predicted samples. Use `zero_division` parameter to control this behavior.\n",
      "  _warn_prf(average, \"true nor predicted\", \"F-score is\", len(true_sum))\n",
      "/home/pruthvish/JRF/RoadNetwork/RoadNetwork_VirtualEnv/lib/python3.8/site-packages/sklearn/linear_model/_logistic.py:444: ConvergenceWarning: lbfgs failed to converge (status=1):\n",
      "STOP: TOTAL NO. of ITERATIONS REACHED LIMIT.\n",
      "\n",
      "Increase the number of iterations (max_iter) or scale the data as shown in:\n",
      "    https://scikit-learn.org/stable/modules/preprocessing.html\n",
      "Please also refer to the documentation for alternative solver options:\n",
      "    https://scikit-learn.org/stable/modules/linear_model.html#logistic-regression\n",
      "  n_iter_i = _check_optimize_result(\n",
      "/home/pruthvish/JRF/RoadNetwork/RoadNetwork_VirtualEnv/lib/python3.8/site-packages/sklearn/metrics/_classification.py:1334: UndefinedMetricWarning: Precision is ill-defined and being set to 0.0 in labels with no predicted samples. Use `zero_division` parameter to control this behavior.\n",
      "  _warn_prf(average, modifier, msg_start, len(result))\n",
      "/home/pruthvish/JRF/RoadNetwork/RoadNetwork_VirtualEnv/lib/python3.8/site-packages/sklearn/metrics/_classification.py:1334: UndefinedMetricWarning: Recall is ill-defined and being set to 0.0 in labels with no true samples. Use `zero_division` parameter to control this behavior.\n",
      "  _warn_prf(average, modifier, msg_start, len(result))\n",
      "/home/pruthvish/JRF/RoadNetwork/RoadNetwork_VirtualEnv/lib/python3.8/site-packages/sklearn/metrics/_classification.py:1599: UndefinedMetricWarning: F-score is ill-defined and being set to 0.0 in labels with no true nor predicted samples. Use `zero_division` parameter to control this behavior.\n",
      "  _warn_prf(average, \"true nor predicted\", \"F-score is\", len(true_sum))\n"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "Feature set-2\n"
     ]
    },
    {
     "name": "stderr",
     "output_type": "stream",
     "text": [
      "/home/pruthvish/JRF/RoadNetwork/RoadNetwork_VirtualEnv/lib/python3.8/site-packages/sklearn/linear_model/_logistic.py:444: ConvergenceWarning: lbfgs failed to converge (status=1):\n",
      "STOP: TOTAL NO. of ITERATIONS REACHED LIMIT.\n",
      "\n",
      "Increase the number of iterations (max_iter) or scale the data as shown in:\n",
      "    https://scikit-learn.org/stable/modules/preprocessing.html\n",
      "Please also refer to the documentation for alternative solver options:\n",
      "    https://scikit-learn.org/stable/modules/linear_model.html#logistic-regression\n",
      "  n_iter_i = _check_optimize_result(\n",
      "/home/pruthvish/JRF/RoadNetwork/RoadNetwork_VirtualEnv/lib/python3.8/site-packages/sklearn/metrics/_classification.py:1334: UndefinedMetricWarning: Precision is ill-defined and being set to 0.0 in labels with no predicted samples. Use `zero_division` parameter to control this behavior.\n",
      "  _warn_prf(average, modifier, msg_start, len(result))\n",
      "/home/pruthvish/JRF/RoadNetwork/RoadNetwork_VirtualEnv/lib/python3.8/site-packages/sklearn/metrics/_classification.py:1334: UndefinedMetricWarning: Recall is ill-defined and being set to 0.0 in labels with no true samples. Use `zero_division` parameter to control this behavior.\n",
      "  _warn_prf(average, modifier, msg_start, len(result))\n",
      "/home/pruthvish/JRF/RoadNetwork/RoadNetwork_VirtualEnv/lib/python3.8/site-packages/sklearn/metrics/_classification.py:1599: UndefinedMetricWarning: F-score is ill-defined and being set to 0.0 in labels with no true nor predicted samples. Use `zero_division` parameter to control this behavior.\n",
      "  _warn_prf(average, \"true nor predicted\", \"F-score is\", len(true_sum))\n",
      "/home/pruthvish/JRF/RoadNetwork/RoadNetwork_VirtualEnv/lib/python3.8/site-packages/sklearn/linear_model/_logistic.py:444: ConvergenceWarning: lbfgs failed to converge (status=1):\n",
      "STOP: TOTAL NO. of ITERATIONS REACHED LIMIT.\n",
      "\n",
      "Increase the number of iterations (max_iter) or scale the data as shown in:\n",
      "    https://scikit-learn.org/stable/modules/preprocessing.html\n",
      "Please also refer to the documentation for alternative solver options:\n",
      "    https://scikit-learn.org/stable/modules/linear_model.html#logistic-regression\n",
      "  n_iter_i = _check_optimize_result(\n",
      "/home/pruthvish/JRF/RoadNetwork/RoadNetwork_VirtualEnv/lib/python3.8/site-packages/sklearn/metrics/_classification.py:1334: UndefinedMetricWarning: Precision is ill-defined and being set to 0.0 in labels with no predicted samples. Use `zero_division` parameter to control this behavior.\n",
      "  _warn_prf(average, modifier, msg_start, len(result))\n",
      "/home/pruthvish/JRF/RoadNetwork/RoadNetwork_VirtualEnv/lib/python3.8/site-packages/sklearn/metrics/_classification.py:1334: UndefinedMetricWarning: Recall is ill-defined and being set to 0.0 in labels with no true samples. Use `zero_division` parameter to control this behavior.\n",
      "  _warn_prf(average, modifier, msg_start, len(result))\n",
      "/home/pruthvish/JRF/RoadNetwork/RoadNetwork_VirtualEnv/lib/python3.8/site-packages/sklearn/metrics/_classification.py:1599: UndefinedMetricWarning: F-score is ill-defined and being set to 0.0 in labels with no true nor predicted samples. Use `zero_division` parameter to control this behavior.\n",
      "  _warn_prf(average, \"true nor predicted\", \"F-score is\", len(true_sum))\n",
      "/home/pruthvish/JRF/RoadNetwork/RoadNetwork_VirtualEnv/lib/python3.8/site-packages/sklearn/linear_model/_logistic.py:444: ConvergenceWarning: lbfgs failed to converge (status=1):\n",
      "STOP: TOTAL NO. of ITERATIONS REACHED LIMIT.\n",
      "\n",
      "Increase the number of iterations (max_iter) or scale the data as shown in:\n",
      "    https://scikit-learn.org/stable/modules/preprocessing.html\n",
      "Please also refer to the documentation for alternative solver options:\n",
      "    https://scikit-learn.org/stable/modules/linear_model.html#logistic-regression\n",
      "  n_iter_i = _check_optimize_result(\n",
      "/home/pruthvish/JRF/RoadNetwork/RoadNetwork_VirtualEnv/lib/python3.8/site-packages/sklearn/metrics/_classification.py:1334: UndefinedMetricWarning: Precision is ill-defined and being set to 0.0 in labels with no predicted samples. Use `zero_division` parameter to control this behavior.\n",
      "  _warn_prf(average, modifier, msg_start, len(result))\n",
      "/home/pruthvish/JRF/RoadNetwork/RoadNetwork_VirtualEnv/lib/python3.8/site-packages/sklearn/metrics/_classification.py:1334: UndefinedMetricWarning: Recall is ill-defined and being set to 0.0 in labels with no true samples. Use `zero_division` parameter to control this behavior.\n",
      "  _warn_prf(average, modifier, msg_start, len(result))\n",
      "/home/pruthvish/JRF/RoadNetwork/RoadNetwork_VirtualEnv/lib/python3.8/site-packages/sklearn/metrics/_classification.py:1599: UndefinedMetricWarning: F-score is ill-defined and being set to 0.0 in labels with no true nor predicted samples. Use `zero_division` parameter to control this behavior.\n",
      "  _warn_prf(average, \"true nor predicted\", \"F-score is\", len(true_sum))\n",
      "/home/pruthvish/JRF/RoadNetwork/RoadNetwork_VirtualEnv/lib/python3.8/site-packages/sklearn/linear_model/_logistic.py:444: ConvergenceWarning: lbfgs failed to converge (status=1):\n",
      "STOP: TOTAL NO. of ITERATIONS REACHED LIMIT.\n",
      "\n",
      "Increase the number of iterations (max_iter) or scale the data as shown in:\n",
      "    https://scikit-learn.org/stable/modules/preprocessing.html\n",
      "Please also refer to the documentation for alternative solver options:\n",
      "    https://scikit-learn.org/stable/modules/linear_model.html#logistic-regression\n",
      "  n_iter_i = _check_optimize_result(\n",
      "/home/pruthvish/JRF/RoadNetwork/RoadNetwork_VirtualEnv/lib/python3.8/site-packages/sklearn/metrics/_classification.py:1334: UndefinedMetricWarning: Precision is ill-defined and being set to 0.0 in labels with no predicted samples. Use `zero_division` parameter to control this behavior.\n",
      "  _warn_prf(average, modifier, msg_start, len(result))\n",
      "/home/pruthvish/JRF/RoadNetwork/RoadNetwork_VirtualEnv/lib/python3.8/site-packages/sklearn/metrics/_classification.py:1334: UndefinedMetricWarning: Recall is ill-defined and being set to 0.0 in labels with no true samples. Use `zero_division` parameter to control this behavior.\n",
      "  _warn_prf(average, modifier, msg_start, len(result))\n",
      "/home/pruthvish/JRF/RoadNetwork/RoadNetwork_VirtualEnv/lib/python3.8/site-packages/sklearn/metrics/_classification.py:1599: UndefinedMetricWarning: F-score is ill-defined and being set to 0.0 in labels with no true nor predicted samples. Use `zero_division` parameter to control this behavior.\n",
      "  _warn_prf(average, \"true nor predicted\", \"F-score is\", len(true_sum))\n",
      "/home/pruthvish/JRF/RoadNetwork/RoadNetwork_VirtualEnv/lib/python3.8/site-packages/sklearn/linear_model/_logistic.py:444: ConvergenceWarning: lbfgs failed to converge (status=1):\n",
      "STOP: TOTAL NO. of ITERATIONS REACHED LIMIT.\n",
      "\n",
      "Increase the number of iterations (max_iter) or scale the data as shown in:\n",
      "    https://scikit-learn.org/stable/modules/preprocessing.html\n",
      "Please also refer to the documentation for alternative solver options:\n",
      "    https://scikit-learn.org/stable/modules/linear_model.html#logistic-regression\n",
      "  n_iter_i = _check_optimize_result(\n",
      "/home/pruthvish/JRF/RoadNetwork/RoadNetwork_VirtualEnv/lib/python3.8/site-packages/sklearn/metrics/_classification.py:1334: UndefinedMetricWarning: Precision is ill-defined and being set to 0.0 in labels with no predicted samples. Use `zero_division` parameter to control this behavior.\n",
      "  _warn_prf(average, modifier, msg_start, len(result))\n",
      "/home/pruthvish/JRF/RoadNetwork/RoadNetwork_VirtualEnv/lib/python3.8/site-packages/sklearn/metrics/_classification.py:1334: UndefinedMetricWarning: Recall is ill-defined and being set to 0.0 in labels with no true samples. Use `zero_division` parameter to control this behavior.\n",
      "  _warn_prf(average, modifier, msg_start, len(result))\n",
      "/home/pruthvish/JRF/RoadNetwork/RoadNetwork_VirtualEnv/lib/python3.8/site-packages/sklearn/metrics/_classification.py:1599: UndefinedMetricWarning: F-score is ill-defined and being set to 0.0 in labels with no true nor predicted samples. Use `zero_division` parameter to control this behavior.\n",
      "  _warn_prf(average, \"true nor predicted\", \"F-score is\", len(true_sum))\n",
      "/home/pruthvish/JRF/RoadNetwork/RoadNetwork_VirtualEnv/lib/python3.8/site-packages/sklearn/linear_model/_logistic.py:444: ConvergenceWarning: lbfgs failed to converge (status=1):\n",
      "STOP: TOTAL NO. of ITERATIONS REACHED LIMIT.\n",
      "\n",
      "Increase the number of iterations (max_iter) or scale the data as shown in:\n",
      "    https://scikit-learn.org/stable/modules/preprocessing.html\n",
      "Please also refer to the documentation for alternative solver options:\n",
      "    https://scikit-learn.org/stable/modules/linear_model.html#logistic-regression\n",
      "  n_iter_i = _check_optimize_result(\n",
      "/home/pruthvish/JRF/RoadNetwork/RoadNetwork_VirtualEnv/lib/python3.8/site-packages/sklearn/metrics/_classification.py:1334: UndefinedMetricWarning: Precision is ill-defined and being set to 0.0 in labels with no predicted samples. Use `zero_division` parameter to control this behavior.\n",
      "  _warn_prf(average, modifier, msg_start, len(result))\n",
      "/home/pruthvish/JRF/RoadNetwork/RoadNetwork_VirtualEnv/lib/python3.8/site-packages/sklearn/metrics/_classification.py:1334: UndefinedMetricWarning: Recall is ill-defined and being set to 0.0 in labels with no true samples. Use `zero_division` parameter to control this behavior.\n",
      "  _warn_prf(average, modifier, msg_start, len(result))\n",
      "/home/pruthvish/JRF/RoadNetwork/RoadNetwork_VirtualEnv/lib/python3.8/site-packages/sklearn/metrics/_classification.py:1599: UndefinedMetricWarning: F-score is ill-defined and being set to 0.0 in labels with no true nor predicted samples. Use `zero_division` parameter to control this behavior.\n",
      "  _warn_prf(average, \"true nor predicted\", \"F-score is\", len(true_sum))\n"
     ]
    },
    {
     "name": "stderr",
     "output_type": "stream",
     "text": [
      "/home/pruthvish/JRF/RoadNetwork/RoadNetwork_VirtualEnv/lib/python3.8/site-packages/sklearn/linear_model/_logistic.py:444: ConvergenceWarning: lbfgs failed to converge (status=1):\n",
      "STOP: TOTAL NO. of ITERATIONS REACHED LIMIT.\n",
      "\n",
      "Increase the number of iterations (max_iter) or scale the data as shown in:\n",
      "    https://scikit-learn.org/stable/modules/preprocessing.html\n",
      "Please also refer to the documentation for alternative solver options:\n",
      "    https://scikit-learn.org/stable/modules/linear_model.html#logistic-regression\n",
      "  n_iter_i = _check_optimize_result(\n",
      "/home/pruthvish/JRF/RoadNetwork/RoadNetwork_VirtualEnv/lib/python3.8/site-packages/sklearn/metrics/_classification.py:1334: UndefinedMetricWarning: Precision is ill-defined and being set to 0.0 in labels with no predicted samples. Use `zero_division` parameter to control this behavior.\n",
      "  _warn_prf(average, modifier, msg_start, len(result))\n",
      "/home/pruthvish/JRF/RoadNetwork/RoadNetwork_VirtualEnv/lib/python3.8/site-packages/sklearn/metrics/_classification.py:1334: UndefinedMetricWarning: Recall is ill-defined and being set to 0.0 in labels with no true samples. Use `zero_division` parameter to control this behavior.\n",
      "  _warn_prf(average, modifier, msg_start, len(result))\n",
      "/home/pruthvish/JRF/RoadNetwork/RoadNetwork_VirtualEnv/lib/python3.8/site-packages/sklearn/metrics/_classification.py:1599: UndefinedMetricWarning: F-score is ill-defined and being set to 0.0 in labels with no true nor predicted samples. Use `zero_division` parameter to control this behavior.\n",
      "  _warn_prf(average, \"true nor predicted\", \"F-score is\", len(true_sum))\n",
      "/home/pruthvish/JRF/RoadNetwork/RoadNetwork_VirtualEnv/lib/python3.8/site-packages/sklearn/linear_model/_logistic.py:444: ConvergenceWarning: lbfgs failed to converge (status=1):\n",
      "STOP: TOTAL NO. of ITERATIONS REACHED LIMIT.\n",
      "\n",
      "Increase the number of iterations (max_iter) or scale the data as shown in:\n",
      "    https://scikit-learn.org/stable/modules/preprocessing.html\n",
      "Please also refer to the documentation for alternative solver options:\n",
      "    https://scikit-learn.org/stable/modules/linear_model.html#logistic-regression\n",
      "  n_iter_i = _check_optimize_result(\n",
      "/home/pruthvish/JRF/RoadNetwork/RoadNetwork_VirtualEnv/lib/python3.8/site-packages/sklearn/metrics/_classification.py:1334: UndefinedMetricWarning: Precision is ill-defined and being set to 0.0 in labels with no predicted samples. Use `zero_division` parameter to control this behavior.\n",
      "  _warn_prf(average, modifier, msg_start, len(result))\n",
      "/home/pruthvish/JRF/RoadNetwork/RoadNetwork_VirtualEnv/lib/python3.8/site-packages/sklearn/metrics/_classification.py:1334: UndefinedMetricWarning: Recall is ill-defined and being set to 0.0 in labels with no true samples. Use `zero_division` parameter to control this behavior.\n",
      "  _warn_prf(average, modifier, msg_start, len(result))\n",
      "/home/pruthvish/JRF/RoadNetwork/RoadNetwork_VirtualEnv/lib/python3.8/site-packages/sklearn/metrics/_classification.py:1599: UndefinedMetricWarning: F-score is ill-defined and being set to 0.0 in labels with no true nor predicted samples. Use `zero_division` parameter to control this behavior.\n",
      "  _warn_prf(average, \"true nor predicted\", \"F-score is\", len(true_sum))\n",
      "/home/pruthvish/JRF/RoadNetwork/RoadNetwork_VirtualEnv/lib/python3.8/site-packages/sklearn/linear_model/_logistic.py:444: ConvergenceWarning: lbfgs failed to converge (status=1):\n",
      "STOP: TOTAL NO. of ITERATIONS REACHED LIMIT.\n",
      "\n",
      "Increase the number of iterations (max_iter) or scale the data as shown in:\n",
      "    https://scikit-learn.org/stable/modules/preprocessing.html\n",
      "Please also refer to the documentation for alternative solver options:\n",
      "    https://scikit-learn.org/stable/modules/linear_model.html#logistic-regression\n",
      "  n_iter_i = _check_optimize_result(\n",
      "/home/pruthvish/JRF/RoadNetwork/RoadNetwork_VirtualEnv/lib/python3.8/site-packages/sklearn/metrics/_classification.py:1334: UndefinedMetricWarning: Precision is ill-defined and being set to 0.0 in labels with no predicted samples. Use `zero_division` parameter to control this behavior.\n",
      "  _warn_prf(average, modifier, msg_start, len(result))\n",
      "/home/pruthvish/JRF/RoadNetwork/RoadNetwork_VirtualEnv/lib/python3.8/site-packages/sklearn/metrics/_classification.py:1334: UndefinedMetricWarning: Recall is ill-defined and being set to 0.0 in labels with no true samples. Use `zero_division` parameter to control this behavior.\n",
      "  _warn_prf(average, modifier, msg_start, len(result))\n",
      "/home/pruthvish/JRF/RoadNetwork/RoadNetwork_VirtualEnv/lib/python3.8/site-packages/sklearn/metrics/_classification.py:1599: UndefinedMetricWarning: F-score is ill-defined and being set to 0.0 in labels with no true nor predicted samples. Use `zero_division` parameter to control this behavior.\n",
      "  _warn_prf(average, \"true nor predicted\", \"F-score is\", len(true_sum))\n",
      "/home/pruthvish/JRF/RoadNetwork/RoadNetwork_VirtualEnv/lib/python3.8/site-packages/sklearn/linear_model/_logistic.py:444: ConvergenceWarning: lbfgs failed to converge (status=1):\n",
      "STOP: TOTAL NO. of ITERATIONS REACHED LIMIT.\n",
      "\n",
      "Increase the number of iterations (max_iter) or scale the data as shown in:\n",
      "    https://scikit-learn.org/stable/modules/preprocessing.html\n",
      "Please also refer to the documentation for alternative solver options:\n",
      "    https://scikit-learn.org/stable/modules/linear_model.html#logistic-regression\n",
      "  n_iter_i = _check_optimize_result(\n",
      "/home/pruthvish/JRF/RoadNetwork/RoadNetwork_VirtualEnv/lib/python3.8/site-packages/sklearn/metrics/_classification.py:1334: UndefinedMetricWarning: Precision is ill-defined and being set to 0.0 in labels with no predicted samples. Use `zero_division` parameter to control this behavior.\n",
      "  _warn_prf(average, modifier, msg_start, len(result))\n",
      "/home/pruthvish/JRF/RoadNetwork/RoadNetwork_VirtualEnv/lib/python3.8/site-packages/sklearn/metrics/_classification.py:1334: UndefinedMetricWarning: Recall is ill-defined and being set to 0.0 in labels with no true samples. Use `zero_division` parameter to control this behavior.\n",
      "  _warn_prf(average, modifier, msg_start, len(result))\n",
      "/home/pruthvish/JRF/RoadNetwork/RoadNetwork_VirtualEnv/lib/python3.8/site-packages/sklearn/metrics/_classification.py:1599: UndefinedMetricWarning: F-score is ill-defined and being set to 0.0 in labels with no true nor predicted samples. Use `zero_division` parameter to control this behavior.\n",
      "  _warn_prf(average, \"true nor predicted\", \"F-score is\", len(true_sum))\n"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "Feature set-3\n"
     ]
    },
    {
     "name": "stderr",
     "output_type": "stream",
     "text": [
      "/home/pruthvish/JRF/RoadNetwork/RoadNetwork_VirtualEnv/lib/python3.8/site-packages/sklearn/linear_model/_logistic.py:444: ConvergenceWarning: lbfgs failed to converge (status=1):\n",
      "STOP: TOTAL NO. of ITERATIONS REACHED LIMIT.\n",
      "\n",
      "Increase the number of iterations (max_iter) or scale the data as shown in:\n",
      "    https://scikit-learn.org/stable/modules/preprocessing.html\n",
      "Please also refer to the documentation for alternative solver options:\n",
      "    https://scikit-learn.org/stable/modules/linear_model.html#logistic-regression\n",
      "  n_iter_i = _check_optimize_result(\n",
      "/home/pruthvish/JRF/RoadNetwork/RoadNetwork_VirtualEnv/lib/python3.8/site-packages/sklearn/metrics/_classification.py:1334: UndefinedMetricWarning: Precision is ill-defined and being set to 0.0 in labels with no predicted samples. Use `zero_division` parameter to control this behavior.\n",
      "  _warn_prf(average, modifier, msg_start, len(result))\n",
      "/home/pruthvish/JRF/RoadNetwork/RoadNetwork_VirtualEnv/lib/python3.8/site-packages/sklearn/metrics/_classification.py:1334: UndefinedMetricWarning: Recall is ill-defined and being set to 0.0 in labels with no true samples. Use `zero_division` parameter to control this behavior.\n",
      "  _warn_prf(average, modifier, msg_start, len(result))\n",
      "/home/pruthvish/JRF/RoadNetwork/RoadNetwork_VirtualEnv/lib/python3.8/site-packages/sklearn/metrics/_classification.py:1599: UndefinedMetricWarning: F-score is ill-defined and being set to 0.0 in labels with no true nor predicted samples. Use `zero_division` parameter to control this behavior.\n",
      "  _warn_prf(average, \"true nor predicted\", \"F-score is\", len(true_sum))\n",
      "/home/pruthvish/JRF/RoadNetwork/RoadNetwork_VirtualEnv/lib/python3.8/site-packages/sklearn/linear_model/_logistic.py:444: ConvergenceWarning: lbfgs failed to converge (status=1):\n",
      "STOP: TOTAL NO. of ITERATIONS REACHED LIMIT.\n",
      "\n",
      "Increase the number of iterations (max_iter) or scale the data as shown in:\n",
      "    https://scikit-learn.org/stable/modules/preprocessing.html\n",
      "Please also refer to the documentation for alternative solver options:\n",
      "    https://scikit-learn.org/stable/modules/linear_model.html#logistic-regression\n",
      "  n_iter_i = _check_optimize_result(\n",
      "/home/pruthvish/JRF/RoadNetwork/RoadNetwork_VirtualEnv/lib/python3.8/site-packages/sklearn/metrics/_classification.py:1334: UndefinedMetricWarning: Precision is ill-defined and being set to 0.0 in labels with no predicted samples. Use `zero_division` parameter to control this behavior.\n",
      "  _warn_prf(average, modifier, msg_start, len(result))\n",
      "/home/pruthvish/JRF/RoadNetwork/RoadNetwork_VirtualEnv/lib/python3.8/site-packages/sklearn/metrics/_classification.py:1334: UndefinedMetricWarning: Recall is ill-defined and being set to 0.0 in labels with no true samples. Use `zero_division` parameter to control this behavior.\n",
      "  _warn_prf(average, modifier, msg_start, len(result))\n",
      "/home/pruthvish/JRF/RoadNetwork/RoadNetwork_VirtualEnv/lib/python3.8/site-packages/sklearn/metrics/_classification.py:1599: UndefinedMetricWarning: F-score is ill-defined and being set to 0.0 in labels with no true nor predicted samples. Use `zero_division` parameter to control this behavior.\n",
      "  _warn_prf(average, \"true nor predicted\", \"F-score is\", len(true_sum))\n",
      "/home/pruthvish/JRF/RoadNetwork/RoadNetwork_VirtualEnv/lib/python3.8/site-packages/sklearn/linear_model/_logistic.py:444: ConvergenceWarning: lbfgs failed to converge (status=1):\n",
      "STOP: TOTAL NO. of ITERATIONS REACHED LIMIT.\n",
      "\n",
      "Increase the number of iterations (max_iter) or scale the data as shown in:\n",
      "    https://scikit-learn.org/stable/modules/preprocessing.html\n",
      "Please also refer to the documentation for alternative solver options:\n",
      "    https://scikit-learn.org/stable/modules/linear_model.html#logistic-regression\n",
      "  n_iter_i = _check_optimize_result(\n",
      "/home/pruthvish/JRF/RoadNetwork/RoadNetwork_VirtualEnv/lib/python3.8/site-packages/sklearn/metrics/_classification.py:1334: UndefinedMetricWarning: Precision is ill-defined and being set to 0.0 in labels with no predicted samples. Use `zero_division` parameter to control this behavior.\n",
      "  _warn_prf(average, modifier, msg_start, len(result))\n",
      "/home/pruthvish/JRF/RoadNetwork/RoadNetwork_VirtualEnv/lib/python3.8/site-packages/sklearn/metrics/_classification.py:1334: UndefinedMetricWarning: Recall is ill-defined and being set to 0.0 in labels with no true samples. Use `zero_division` parameter to control this behavior.\n",
      "  _warn_prf(average, modifier, msg_start, len(result))\n",
      "/home/pruthvish/JRF/RoadNetwork/RoadNetwork_VirtualEnv/lib/python3.8/site-packages/sklearn/metrics/_classification.py:1599: UndefinedMetricWarning: F-score is ill-defined and being set to 0.0 in labels with no true nor predicted samples. Use `zero_division` parameter to control this behavior.\n",
      "  _warn_prf(average, \"true nor predicted\", \"F-score is\", len(true_sum))\n",
      "/home/pruthvish/JRF/RoadNetwork/RoadNetwork_VirtualEnv/lib/python3.8/site-packages/sklearn/linear_model/_logistic.py:444: ConvergenceWarning: lbfgs failed to converge (status=1):\n",
      "STOP: TOTAL NO. of ITERATIONS REACHED LIMIT.\n",
      "\n",
      "Increase the number of iterations (max_iter) or scale the data as shown in:\n",
      "    https://scikit-learn.org/stable/modules/preprocessing.html\n",
      "Please also refer to the documentation for alternative solver options:\n",
      "    https://scikit-learn.org/stable/modules/linear_model.html#logistic-regression\n",
      "  n_iter_i = _check_optimize_result(\n",
      "/home/pruthvish/JRF/RoadNetwork/RoadNetwork_VirtualEnv/lib/python3.8/site-packages/sklearn/metrics/_classification.py:1334: UndefinedMetricWarning: Precision is ill-defined and being set to 0.0 in labels with no predicted samples. Use `zero_division` parameter to control this behavior.\n",
      "  _warn_prf(average, modifier, msg_start, len(result))\n",
      "/home/pruthvish/JRF/RoadNetwork/RoadNetwork_VirtualEnv/lib/python3.8/site-packages/sklearn/metrics/_classification.py:1334: UndefinedMetricWarning: Recall is ill-defined and being set to 0.0 in labels with no true samples. Use `zero_division` parameter to control this behavior.\n",
      "  _warn_prf(average, modifier, msg_start, len(result))\n",
      "/home/pruthvish/JRF/RoadNetwork/RoadNetwork_VirtualEnv/lib/python3.8/site-packages/sklearn/metrics/_classification.py:1599: UndefinedMetricWarning: F-score is ill-defined and being set to 0.0 in labels with no true nor predicted samples. Use `zero_division` parameter to control this behavior.\n",
      "  _warn_prf(average, \"true nor predicted\", \"F-score is\", len(true_sum))\n",
      "/home/pruthvish/JRF/RoadNetwork/RoadNetwork_VirtualEnv/lib/python3.8/site-packages/sklearn/linear_model/_logistic.py:444: ConvergenceWarning: lbfgs failed to converge (status=1):\n",
      "STOP: TOTAL NO. of ITERATIONS REACHED LIMIT.\n",
      "\n",
      "Increase the number of iterations (max_iter) or scale the data as shown in:\n",
      "    https://scikit-learn.org/stable/modules/preprocessing.html\n",
      "Please also refer to the documentation for alternative solver options:\n",
      "    https://scikit-learn.org/stable/modules/linear_model.html#logistic-regression\n",
      "  n_iter_i = _check_optimize_result(\n",
      "/home/pruthvish/JRF/RoadNetwork/RoadNetwork_VirtualEnv/lib/python3.8/site-packages/sklearn/metrics/_classification.py:1334: UndefinedMetricWarning: Precision is ill-defined and being set to 0.0 in labels with no predicted samples. Use `zero_division` parameter to control this behavior.\n",
      "  _warn_prf(average, modifier, msg_start, len(result))\n",
      "/home/pruthvish/JRF/RoadNetwork/RoadNetwork_VirtualEnv/lib/python3.8/site-packages/sklearn/metrics/_classification.py:1334: UndefinedMetricWarning: Recall is ill-defined and being set to 0.0 in labels with no true samples. Use `zero_division` parameter to control this behavior.\n",
      "  _warn_prf(average, modifier, msg_start, len(result))\n",
      "/home/pruthvish/JRF/RoadNetwork/RoadNetwork_VirtualEnv/lib/python3.8/site-packages/sklearn/metrics/_classification.py:1599: UndefinedMetricWarning: F-score is ill-defined and being set to 0.0 in labels with no true nor predicted samples. Use `zero_division` parameter to control this behavior.\n",
      "  _warn_prf(average, \"true nor predicted\", \"F-score is\", len(true_sum))\n",
      "/home/pruthvish/JRF/RoadNetwork/RoadNetwork_VirtualEnv/lib/python3.8/site-packages/sklearn/linear_model/_logistic.py:444: ConvergenceWarning: lbfgs failed to converge (status=1):\n",
      "STOP: TOTAL NO. of ITERATIONS REACHED LIMIT.\n",
      "\n",
      "Increase the number of iterations (max_iter) or scale the data as shown in:\n",
      "    https://scikit-learn.org/stable/modules/preprocessing.html\n",
      "Please also refer to the documentation for alternative solver options:\n",
      "    https://scikit-learn.org/stable/modules/linear_model.html#logistic-regression\n",
      "  n_iter_i = _check_optimize_result(\n",
      "/home/pruthvish/JRF/RoadNetwork/RoadNetwork_VirtualEnv/lib/python3.8/site-packages/sklearn/metrics/_classification.py:1334: UndefinedMetricWarning: Precision is ill-defined and being set to 0.0 in labels with no predicted samples. Use `zero_division` parameter to control this behavior.\n",
      "  _warn_prf(average, modifier, msg_start, len(result))\n",
      "/home/pruthvish/JRF/RoadNetwork/RoadNetwork_VirtualEnv/lib/python3.8/site-packages/sklearn/metrics/_classification.py:1334: UndefinedMetricWarning: Recall is ill-defined and being set to 0.0 in labels with no true samples. Use `zero_division` parameter to control this behavior.\n",
      "  _warn_prf(average, modifier, msg_start, len(result))\n",
      "/home/pruthvish/JRF/RoadNetwork/RoadNetwork_VirtualEnv/lib/python3.8/site-packages/sklearn/metrics/_classification.py:1599: UndefinedMetricWarning: F-score is ill-defined and being set to 0.0 in labels with no true nor predicted samples. Use `zero_division` parameter to control this behavior.\n",
      "  _warn_prf(average, \"true nor predicted\", \"F-score is\", len(true_sum))\n"
     ]
    },
    {
     "name": "stderr",
     "output_type": "stream",
     "text": [
      "/home/pruthvish/JRF/RoadNetwork/RoadNetwork_VirtualEnv/lib/python3.8/site-packages/sklearn/linear_model/_logistic.py:444: ConvergenceWarning: lbfgs failed to converge (status=1):\n",
      "STOP: TOTAL NO. of ITERATIONS REACHED LIMIT.\n",
      "\n",
      "Increase the number of iterations (max_iter) or scale the data as shown in:\n",
      "    https://scikit-learn.org/stable/modules/preprocessing.html\n",
      "Please also refer to the documentation for alternative solver options:\n",
      "    https://scikit-learn.org/stable/modules/linear_model.html#logistic-regression\n",
      "  n_iter_i = _check_optimize_result(\n",
      "/home/pruthvish/JRF/RoadNetwork/RoadNetwork_VirtualEnv/lib/python3.8/site-packages/sklearn/metrics/_classification.py:1334: UndefinedMetricWarning: Precision is ill-defined and being set to 0.0 in labels with no predicted samples. Use `zero_division` parameter to control this behavior.\n",
      "  _warn_prf(average, modifier, msg_start, len(result))\n",
      "/home/pruthvish/JRF/RoadNetwork/RoadNetwork_VirtualEnv/lib/python3.8/site-packages/sklearn/metrics/_classification.py:1334: UndefinedMetricWarning: Recall is ill-defined and being set to 0.0 in labels with no true samples. Use `zero_division` parameter to control this behavior.\n",
      "  _warn_prf(average, modifier, msg_start, len(result))\n",
      "/home/pruthvish/JRF/RoadNetwork/RoadNetwork_VirtualEnv/lib/python3.8/site-packages/sklearn/metrics/_classification.py:1599: UndefinedMetricWarning: F-score is ill-defined and being set to 0.0 in labels with no true nor predicted samples. Use `zero_division` parameter to control this behavior.\n",
      "  _warn_prf(average, \"true nor predicted\", \"F-score is\", len(true_sum))\n",
      "/home/pruthvish/JRF/RoadNetwork/RoadNetwork_VirtualEnv/lib/python3.8/site-packages/sklearn/linear_model/_logistic.py:444: ConvergenceWarning: lbfgs failed to converge (status=1):\n",
      "STOP: TOTAL NO. of ITERATIONS REACHED LIMIT.\n",
      "\n",
      "Increase the number of iterations (max_iter) or scale the data as shown in:\n",
      "    https://scikit-learn.org/stable/modules/preprocessing.html\n",
      "Please also refer to the documentation for alternative solver options:\n",
      "    https://scikit-learn.org/stable/modules/linear_model.html#logistic-regression\n",
      "  n_iter_i = _check_optimize_result(\n",
      "/home/pruthvish/JRF/RoadNetwork/RoadNetwork_VirtualEnv/lib/python3.8/site-packages/sklearn/metrics/_classification.py:1334: UndefinedMetricWarning: Precision is ill-defined and being set to 0.0 in labels with no predicted samples. Use `zero_division` parameter to control this behavior.\n",
      "  _warn_prf(average, modifier, msg_start, len(result))\n",
      "/home/pruthvish/JRF/RoadNetwork/RoadNetwork_VirtualEnv/lib/python3.8/site-packages/sklearn/metrics/_classification.py:1334: UndefinedMetricWarning: Recall is ill-defined and being set to 0.0 in labels with no true samples. Use `zero_division` parameter to control this behavior.\n",
      "  _warn_prf(average, modifier, msg_start, len(result))\n",
      "/home/pruthvish/JRF/RoadNetwork/RoadNetwork_VirtualEnv/lib/python3.8/site-packages/sklearn/metrics/_classification.py:1599: UndefinedMetricWarning: F-score is ill-defined and being set to 0.0 in labels with no true nor predicted samples. Use `zero_division` parameter to control this behavior.\n",
      "  _warn_prf(average, \"true nor predicted\", \"F-score is\", len(true_sum))\n",
      "/home/pruthvish/JRF/RoadNetwork/RoadNetwork_VirtualEnv/lib/python3.8/site-packages/sklearn/linear_model/_logistic.py:444: ConvergenceWarning: lbfgs failed to converge (status=1):\n",
      "STOP: TOTAL NO. of ITERATIONS REACHED LIMIT.\n",
      "\n",
      "Increase the number of iterations (max_iter) or scale the data as shown in:\n",
      "    https://scikit-learn.org/stable/modules/preprocessing.html\n",
      "Please also refer to the documentation for alternative solver options:\n",
      "    https://scikit-learn.org/stable/modules/linear_model.html#logistic-regression\n",
      "  n_iter_i = _check_optimize_result(\n",
      "/home/pruthvish/JRF/RoadNetwork/RoadNetwork_VirtualEnv/lib/python3.8/site-packages/sklearn/metrics/_classification.py:1334: UndefinedMetricWarning: Precision is ill-defined and being set to 0.0 in labels with no predicted samples. Use `zero_division` parameter to control this behavior.\n",
      "  _warn_prf(average, modifier, msg_start, len(result))\n",
      "/home/pruthvish/JRF/RoadNetwork/RoadNetwork_VirtualEnv/lib/python3.8/site-packages/sklearn/metrics/_classification.py:1334: UndefinedMetricWarning: Recall is ill-defined and being set to 0.0 in labels with no true samples. Use `zero_division` parameter to control this behavior.\n",
      "  _warn_prf(average, modifier, msg_start, len(result))\n",
      "/home/pruthvish/JRF/RoadNetwork/RoadNetwork_VirtualEnv/lib/python3.8/site-packages/sklearn/metrics/_classification.py:1599: UndefinedMetricWarning: F-score is ill-defined and being set to 0.0 in labels with no true nor predicted samples. Use `zero_division` parameter to control this behavior.\n",
      "  _warn_prf(average, \"true nor predicted\", \"F-score is\", len(true_sum))\n",
      "/home/pruthvish/JRF/RoadNetwork/RoadNetwork_VirtualEnv/lib/python3.8/site-packages/sklearn/linear_model/_logistic.py:444: ConvergenceWarning: lbfgs failed to converge (status=1):\n",
      "STOP: TOTAL NO. of ITERATIONS REACHED LIMIT.\n",
      "\n",
      "Increase the number of iterations (max_iter) or scale the data as shown in:\n",
      "    https://scikit-learn.org/stable/modules/preprocessing.html\n",
      "Please also refer to the documentation for alternative solver options:\n",
      "    https://scikit-learn.org/stable/modules/linear_model.html#logistic-regression\n",
      "  n_iter_i = _check_optimize_result(\n",
      "/home/pruthvish/JRF/RoadNetwork/RoadNetwork_VirtualEnv/lib/python3.8/site-packages/sklearn/metrics/_classification.py:1334: UndefinedMetricWarning: Precision is ill-defined and being set to 0.0 in labels with no predicted samples. Use `zero_division` parameter to control this behavior.\n",
      "  _warn_prf(average, modifier, msg_start, len(result))\n",
      "/home/pruthvish/JRF/RoadNetwork/RoadNetwork_VirtualEnv/lib/python3.8/site-packages/sklearn/metrics/_classification.py:1334: UndefinedMetricWarning: Recall is ill-defined and being set to 0.0 in labels with no true samples. Use `zero_division` parameter to control this behavior.\n",
      "  _warn_prf(average, modifier, msg_start, len(result))\n",
      "/home/pruthvish/JRF/RoadNetwork/RoadNetwork_VirtualEnv/lib/python3.8/site-packages/sklearn/metrics/_classification.py:1599: UndefinedMetricWarning: F-score is ill-defined and being set to 0.0 in labels with no true nor predicted samples. Use `zero_division` parameter to control this behavior.\n",
      "  _warn_prf(average, \"true nor predicted\", \"F-score is\", len(true_sum))\n"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "Feature set-4\n"
     ]
    },
    {
     "name": "stderr",
     "output_type": "stream",
     "text": [
      "/home/pruthvish/JRF/RoadNetwork/RoadNetwork_VirtualEnv/lib/python3.8/site-packages/sklearn/linear_model/_logistic.py:444: ConvergenceWarning: lbfgs failed to converge (status=1):\n",
      "STOP: TOTAL NO. of ITERATIONS REACHED LIMIT.\n",
      "\n",
      "Increase the number of iterations (max_iter) or scale the data as shown in:\n",
      "    https://scikit-learn.org/stable/modules/preprocessing.html\n",
      "Please also refer to the documentation for alternative solver options:\n",
      "    https://scikit-learn.org/stable/modules/linear_model.html#logistic-regression\n",
      "  n_iter_i = _check_optimize_result(\n",
      "/home/pruthvish/JRF/RoadNetwork/RoadNetwork_VirtualEnv/lib/python3.8/site-packages/sklearn/metrics/_classification.py:1334: UndefinedMetricWarning: Precision is ill-defined and being set to 0.0 in labels with no predicted samples. Use `zero_division` parameter to control this behavior.\n",
      "  _warn_prf(average, modifier, msg_start, len(result))\n",
      "/home/pruthvish/JRF/RoadNetwork/RoadNetwork_VirtualEnv/lib/python3.8/site-packages/sklearn/metrics/_classification.py:1334: UndefinedMetricWarning: Recall is ill-defined and being set to 0.0 in labels with no true samples. Use `zero_division` parameter to control this behavior.\n",
      "  _warn_prf(average, modifier, msg_start, len(result))\n",
      "/home/pruthvish/JRF/RoadNetwork/RoadNetwork_VirtualEnv/lib/python3.8/site-packages/sklearn/metrics/_classification.py:1599: UndefinedMetricWarning: F-score is ill-defined and being set to 0.0 in labels with no true nor predicted samples. Use `zero_division` parameter to control this behavior.\n",
      "  _warn_prf(average, \"true nor predicted\", \"F-score is\", len(true_sum))\n",
      "/home/pruthvish/JRF/RoadNetwork/RoadNetwork_VirtualEnv/lib/python3.8/site-packages/sklearn/linear_model/_logistic.py:444: ConvergenceWarning: lbfgs failed to converge (status=1):\n",
      "STOP: TOTAL NO. of ITERATIONS REACHED LIMIT.\n",
      "\n",
      "Increase the number of iterations (max_iter) or scale the data as shown in:\n",
      "    https://scikit-learn.org/stable/modules/preprocessing.html\n",
      "Please also refer to the documentation for alternative solver options:\n",
      "    https://scikit-learn.org/stable/modules/linear_model.html#logistic-regression\n",
      "  n_iter_i = _check_optimize_result(\n",
      "/home/pruthvish/JRF/RoadNetwork/RoadNetwork_VirtualEnv/lib/python3.8/site-packages/sklearn/metrics/_classification.py:1334: UndefinedMetricWarning: Precision is ill-defined and being set to 0.0 in labels with no predicted samples. Use `zero_division` parameter to control this behavior.\n",
      "  _warn_prf(average, modifier, msg_start, len(result))\n",
      "/home/pruthvish/JRF/RoadNetwork/RoadNetwork_VirtualEnv/lib/python3.8/site-packages/sklearn/metrics/_classification.py:1334: UndefinedMetricWarning: Recall is ill-defined and being set to 0.0 in labels with no true samples. Use `zero_division` parameter to control this behavior.\n",
      "  _warn_prf(average, modifier, msg_start, len(result))\n",
      "/home/pruthvish/JRF/RoadNetwork/RoadNetwork_VirtualEnv/lib/python3.8/site-packages/sklearn/metrics/_classification.py:1599: UndefinedMetricWarning: F-score is ill-defined and being set to 0.0 in labels with no true nor predicted samples. Use `zero_division` parameter to control this behavior.\n",
      "  _warn_prf(average, \"true nor predicted\", \"F-score is\", len(true_sum))\n",
      "/home/pruthvish/JRF/RoadNetwork/RoadNetwork_VirtualEnv/lib/python3.8/site-packages/sklearn/linear_model/_logistic.py:444: ConvergenceWarning: lbfgs failed to converge (status=1):\n",
      "STOP: TOTAL NO. of ITERATIONS REACHED LIMIT.\n",
      "\n",
      "Increase the number of iterations (max_iter) or scale the data as shown in:\n",
      "    https://scikit-learn.org/stable/modules/preprocessing.html\n",
      "Please also refer to the documentation for alternative solver options:\n",
      "    https://scikit-learn.org/stable/modules/linear_model.html#logistic-regression\n",
      "  n_iter_i = _check_optimize_result(\n",
      "/home/pruthvish/JRF/RoadNetwork/RoadNetwork_VirtualEnv/lib/python3.8/site-packages/sklearn/metrics/_classification.py:1334: UndefinedMetricWarning: Precision is ill-defined and being set to 0.0 in labels with no predicted samples. Use `zero_division` parameter to control this behavior.\n",
      "  _warn_prf(average, modifier, msg_start, len(result))\n",
      "/home/pruthvish/JRF/RoadNetwork/RoadNetwork_VirtualEnv/lib/python3.8/site-packages/sklearn/metrics/_classification.py:1334: UndefinedMetricWarning: Recall is ill-defined and being set to 0.0 in labels with no true samples. Use `zero_division` parameter to control this behavior.\n",
      "  _warn_prf(average, modifier, msg_start, len(result))\n",
      "/home/pruthvish/JRF/RoadNetwork/RoadNetwork_VirtualEnv/lib/python3.8/site-packages/sklearn/metrics/_classification.py:1599: UndefinedMetricWarning: F-score is ill-defined and being set to 0.0 in labels with no true nor predicted samples. Use `zero_division` parameter to control this behavior.\n",
      "  _warn_prf(average, \"true nor predicted\", \"F-score is\", len(true_sum))\n",
      "/home/pruthvish/JRF/RoadNetwork/RoadNetwork_VirtualEnv/lib/python3.8/site-packages/sklearn/linear_model/_logistic.py:444: ConvergenceWarning: lbfgs failed to converge (status=1):\n",
      "STOP: TOTAL NO. of ITERATIONS REACHED LIMIT.\n",
      "\n",
      "Increase the number of iterations (max_iter) or scale the data as shown in:\n",
      "    https://scikit-learn.org/stable/modules/preprocessing.html\n",
      "Please also refer to the documentation for alternative solver options:\n",
      "    https://scikit-learn.org/stable/modules/linear_model.html#logistic-regression\n",
      "  n_iter_i = _check_optimize_result(\n",
      "/home/pruthvish/JRF/RoadNetwork/RoadNetwork_VirtualEnv/lib/python3.8/site-packages/sklearn/metrics/_classification.py:1334: UndefinedMetricWarning: Precision is ill-defined and being set to 0.0 in labels with no predicted samples. Use `zero_division` parameter to control this behavior.\n",
      "  _warn_prf(average, modifier, msg_start, len(result))\n",
      "/home/pruthvish/JRF/RoadNetwork/RoadNetwork_VirtualEnv/lib/python3.8/site-packages/sklearn/metrics/_classification.py:1334: UndefinedMetricWarning: Recall is ill-defined and being set to 0.0 in labels with no true samples. Use `zero_division` parameter to control this behavior.\n",
      "  _warn_prf(average, modifier, msg_start, len(result))\n",
      "/home/pruthvish/JRF/RoadNetwork/RoadNetwork_VirtualEnv/lib/python3.8/site-packages/sklearn/metrics/_classification.py:1599: UndefinedMetricWarning: F-score is ill-defined and being set to 0.0 in labels with no true nor predicted samples. Use `zero_division` parameter to control this behavior.\n",
      "  _warn_prf(average, \"true nor predicted\", \"F-score is\", len(true_sum))\n",
      "/home/pruthvish/JRF/RoadNetwork/RoadNetwork_VirtualEnv/lib/python3.8/site-packages/sklearn/linear_model/_logistic.py:444: ConvergenceWarning: lbfgs failed to converge (status=1):\n",
      "STOP: TOTAL NO. of ITERATIONS REACHED LIMIT.\n",
      "\n",
      "Increase the number of iterations (max_iter) or scale the data as shown in:\n",
      "    https://scikit-learn.org/stable/modules/preprocessing.html\n",
      "Please also refer to the documentation for alternative solver options:\n",
      "    https://scikit-learn.org/stable/modules/linear_model.html#logistic-regression\n",
      "  n_iter_i = _check_optimize_result(\n",
      "/home/pruthvish/JRF/RoadNetwork/RoadNetwork_VirtualEnv/lib/python3.8/site-packages/sklearn/metrics/_classification.py:1334: UndefinedMetricWarning: Precision is ill-defined and being set to 0.0 in labels with no predicted samples. Use `zero_division` parameter to control this behavior.\n",
      "  _warn_prf(average, modifier, msg_start, len(result))\n",
      "/home/pruthvish/JRF/RoadNetwork/RoadNetwork_VirtualEnv/lib/python3.8/site-packages/sklearn/metrics/_classification.py:1334: UndefinedMetricWarning: Recall is ill-defined and being set to 0.0 in labels with no true samples. Use `zero_division` parameter to control this behavior.\n",
      "  _warn_prf(average, modifier, msg_start, len(result))\n",
      "/home/pruthvish/JRF/RoadNetwork/RoadNetwork_VirtualEnv/lib/python3.8/site-packages/sklearn/metrics/_classification.py:1599: UndefinedMetricWarning: F-score is ill-defined and being set to 0.0 in labels with no true nor predicted samples. Use `zero_division` parameter to control this behavior.\n",
      "  _warn_prf(average, \"true nor predicted\", \"F-score is\", len(true_sum))\n",
      "/home/pruthvish/JRF/RoadNetwork/RoadNetwork_VirtualEnv/lib/python3.8/site-packages/sklearn/linear_model/_logistic.py:444: ConvergenceWarning: lbfgs failed to converge (status=1):\n",
      "STOP: TOTAL NO. of ITERATIONS REACHED LIMIT.\n",
      "\n",
      "Increase the number of iterations (max_iter) or scale the data as shown in:\n",
      "    https://scikit-learn.org/stable/modules/preprocessing.html\n",
      "Please also refer to the documentation for alternative solver options:\n",
      "    https://scikit-learn.org/stable/modules/linear_model.html#logistic-regression\n",
      "  n_iter_i = _check_optimize_result(\n",
      "/home/pruthvish/JRF/RoadNetwork/RoadNetwork_VirtualEnv/lib/python3.8/site-packages/sklearn/metrics/_classification.py:1334: UndefinedMetricWarning: Precision is ill-defined and being set to 0.0 in labels with no predicted samples. Use `zero_division` parameter to control this behavior.\n",
      "  _warn_prf(average, modifier, msg_start, len(result))\n",
      "/home/pruthvish/JRF/RoadNetwork/RoadNetwork_VirtualEnv/lib/python3.8/site-packages/sklearn/metrics/_classification.py:1334: UndefinedMetricWarning: Recall is ill-defined and being set to 0.0 in labels with no true samples. Use `zero_division` parameter to control this behavior.\n",
      "  _warn_prf(average, modifier, msg_start, len(result))\n",
      "/home/pruthvish/JRF/RoadNetwork/RoadNetwork_VirtualEnv/lib/python3.8/site-packages/sklearn/metrics/_classification.py:1599: UndefinedMetricWarning: F-score is ill-defined and being set to 0.0 in labels with no true nor predicted samples. Use `zero_division` parameter to control this behavior.\n",
      "  _warn_prf(average, \"true nor predicted\", \"F-score is\", len(true_sum))\n"
     ]
    },
    {
     "name": "stderr",
     "output_type": "stream",
     "text": [
      "/home/pruthvish/JRF/RoadNetwork/RoadNetwork_VirtualEnv/lib/python3.8/site-packages/sklearn/linear_model/_logistic.py:444: ConvergenceWarning: lbfgs failed to converge (status=1):\n",
      "STOP: TOTAL NO. of ITERATIONS REACHED LIMIT.\n",
      "\n",
      "Increase the number of iterations (max_iter) or scale the data as shown in:\n",
      "    https://scikit-learn.org/stable/modules/preprocessing.html\n",
      "Please also refer to the documentation for alternative solver options:\n",
      "    https://scikit-learn.org/stable/modules/linear_model.html#logistic-regression\n",
      "  n_iter_i = _check_optimize_result(\n",
      "/home/pruthvish/JRF/RoadNetwork/RoadNetwork_VirtualEnv/lib/python3.8/site-packages/sklearn/metrics/_classification.py:1334: UndefinedMetricWarning: Precision is ill-defined and being set to 0.0 in labels with no predicted samples. Use `zero_division` parameter to control this behavior.\n",
      "  _warn_prf(average, modifier, msg_start, len(result))\n",
      "/home/pruthvish/JRF/RoadNetwork/RoadNetwork_VirtualEnv/lib/python3.8/site-packages/sklearn/metrics/_classification.py:1334: UndefinedMetricWarning: Recall is ill-defined and being set to 0.0 in labels with no true samples. Use `zero_division` parameter to control this behavior.\n",
      "  _warn_prf(average, modifier, msg_start, len(result))\n",
      "/home/pruthvish/JRF/RoadNetwork/RoadNetwork_VirtualEnv/lib/python3.8/site-packages/sklearn/metrics/_classification.py:1599: UndefinedMetricWarning: F-score is ill-defined and being set to 0.0 in labels with no true nor predicted samples. Use `zero_division` parameter to control this behavior.\n",
      "  _warn_prf(average, \"true nor predicted\", \"F-score is\", len(true_sum))\n",
      "/home/pruthvish/JRF/RoadNetwork/RoadNetwork_VirtualEnv/lib/python3.8/site-packages/sklearn/linear_model/_logistic.py:444: ConvergenceWarning: lbfgs failed to converge (status=1):\n",
      "STOP: TOTAL NO. of ITERATIONS REACHED LIMIT.\n",
      "\n",
      "Increase the number of iterations (max_iter) or scale the data as shown in:\n",
      "    https://scikit-learn.org/stable/modules/preprocessing.html\n",
      "Please also refer to the documentation for alternative solver options:\n",
      "    https://scikit-learn.org/stable/modules/linear_model.html#logistic-regression\n",
      "  n_iter_i = _check_optimize_result(\n",
      "/home/pruthvish/JRF/RoadNetwork/RoadNetwork_VirtualEnv/lib/python3.8/site-packages/sklearn/metrics/_classification.py:1334: UndefinedMetricWarning: Precision is ill-defined and being set to 0.0 in labels with no predicted samples. Use `zero_division` parameter to control this behavior.\n",
      "  _warn_prf(average, modifier, msg_start, len(result))\n",
      "/home/pruthvish/JRF/RoadNetwork/RoadNetwork_VirtualEnv/lib/python3.8/site-packages/sklearn/metrics/_classification.py:1334: UndefinedMetricWarning: Recall is ill-defined and being set to 0.0 in labels with no true samples. Use `zero_division` parameter to control this behavior.\n",
      "  _warn_prf(average, modifier, msg_start, len(result))\n",
      "/home/pruthvish/JRF/RoadNetwork/RoadNetwork_VirtualEnv/lib/python3.8/site-packages/sklearn/metrics/_classification.py:1599: UndefinedMetricWarning: F-score is ill-defined and being set to 0.0 in labels with no true nor predicted samples. Use `zero_division` parameter to control this behavior.\n",
      "  _warn_prf(average, \"true nor predicted\", \"F-score is\", len(true_sum))\n",
      "/home/pruthvish/JRF/RoadNetwork/RoadNetwork_VirtualEnv/lib/python3.8/site-packages/sklearn/linear_model/_logistic.py:444: ConvergenceWarning: lbfgs failed to converge (status=1):\n",
      "STOP: TOTAL NO. of ITERATIONS REACHED LIMIT.\n",
      "\n",
      "Increase the number of iterations (max_iter) or scale the data as shown in:\n",
      "    https://scikit-learn.org/stable/modules/preprocessing.html\n",
      "Please also refer to the documentation for alternative solver options:\n",
      "    https://scikit-learn.org/stable/modules/linear_model.html#logistic-regression\n",
      "  n_iter_i = _check_optimize_result(\n",
      "/home/pruthvish/JRF/RoadNetwork/RoadNetwork_VirtualEnv/lib/python3.8/site-packages/sklearn/metrics/_classification.py:1334: UndefinedMetricWarning: Precision is ill-defined and being set to 0.0 in labels with no predicted samples. Use `zero_division` parameter to control this behavior.\n",
      "  _warn_prf(average, modifier, msg_start, len(result))\n",
      "/home/pruthvish/JRF/RoadNetwork/RoadNetwork_VirtualEnv/lib/python3.8/site-packages/sklearn/metrics/_classification.py:1334: UndefinedMetricWarning: Recall is ill-defined and being set to 0.0 in labels with no true samples. Use `zero_division` parameter to control this behavior.\n",
      "  _warn_prf(average, modifier, msg_start, len(result))\n",
      "/home/pruthvish/JRF/RoadNetwork/RoadNetwork_VirtualEnv/lib/python3.8/site-packages/sklearn/metrics/_classification.py:1599: UndefinedMetricWarning: F-score is ill-defined and being set to 0.0 in labels with no true nor predicted samples. Use `zero_division` parameter to control this behavior.\n",
      "  _warn_prf(average, \"true nor predicted\", \"F-score is\", len(true_sum))\n",
      "/home/pruthvish/JRF/RoadNetwork/RoadNetwork_VirtualEnv/lib/python3.8/site-packages/sklearn/linear_model/_logistic.py:444: ConvergenceWarning: lbfgs failed to converge (status=1):\n",
      "STOP: TOTAL NO. of ITERATIONS REACHED LIMIT.\n",
      "\n",
      "Increase the number of iterations (max_iter) or scale the data as shown in:\n",
      "    https://scikit-learn.org/stable/modules/preprocessing.html\n",
      "Please also refer to the documentation for alternative solver options:\n",
      "    https://scikit-learn.org/stable/modules/linear_model.html#logistic-regression\n",
      "  n_iter_i = _check_optimize_result(\n",
      "/home/pruthvish/JRF/RoadNetwork/RoadNetwork_VirtualEnv/lib/python3.8/site-packages/sklearn/metrics/_classification.py:1334: UndefinedMetricWarning: Precision is ill-defined and being set to 0.0 in labels with no predicted samples. Use `zero_division` parameter to control this behavior.\n",
      "  _warn_prf(average, modifier, msg_start, len(result))\n",
      "/home/pruthvish/JRF/RoadNetwork/RoadNetwork_VirtualEnv/lib/python3.8/site-packages/sklearn/metrics/_classification.py:1334: UndefinedMetricWarning: Recall is ill-defined and being set to 0.0 in labels with no true samples. Use `zero_division` parameter to control this behavior.\n",
      "  _warn_prf(average, modifier, msg_start, len(result))\n",
      "/home/pruthvish/JRF/RoadNetwork/RoadNetwork_VirtualEnv/lib/python3.8/site-packages/sklearn/metrics/_classification.py:1599: UndefinedMetricWarning: F-score is ill-defined and being set to 0.0 in labels with no true nor predicted samples. Use `zero_division` parameter to control this behavior.\n",
      "  _warn_prf(average, \"true nor predicted\", \"F-score is\", len(true_sum))\n"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "Classifier, ClassifierName RandomForestClassifier(max_depth=20) RF\n",
      "Feature set-1\n"
     ]
    },
    {
     "name": "stderr",
     "output_type": "stream",
     "text": [
      "/home/pruthvish/JRF/RoadNetwork/RoadNetwork_VirtualEnv/lib/python3.8/site-packages/sklearn/metrics/_classification.py:1334: UndefinedMetricWarning: Precision is ill-defined and being set to 0.0 in labels with no predicted samples. Use `zero_division` parameter to control this behavior.\n",
      "  _warn_prf(average, modifier, msg_start, len(result))\n",
      "/home/pruthvish/JRF/RoadNetwork/RoadNetwork_VirtualEnv/lib/python3.8/site-packages/sklearn/metrics/_classification.py:1334: UndefinedMetricWarning: Recall is ill-defined and being set to 0.0 in labels with no true samples. Use `zero_division` parameter to control this behavior.\n",
      "  _warn_prf(average, modifier, msg_start, len(result))\n",
      "/home/pruthvish/JRF/RoadNetwork/RoadNetwork_VirtualEnv/lib/python3.8/site-packages/sklearn/metrics/_classification.py:1599: UndefinedMetricWarning: F-score is ill-defined and being set to 0.0 in labels with no true nor predicted samples. Use `zero_division` parameter to control this behavior.\n",
      "  _warn_prf(average, \"true nor predicted\", \"F-score is\", len(true_sum))\n",
      "/home/pruthvish/JRF/RoadNetwork/RoadNetwork_VirtualEnv/lib/python3.8/site-packages/sklearn/metrics/_classification.py:1334: UndefinedMetricWarning: Precision is ill-defined and being set to 0.0 in labels with no predicted samples. Use `zero_division` parameter to control this behavior.\n",
      "  _warn_prf(average, modifier, msg_start, len(result))\n",
      "/home/pruthvish/JRF/RoadNetwork/RoadNetwork_VirtualEnv/lib/python3.8/site-packages/sklearn/metrics/_classification.py:1334: UndefinedMetricWarning: Recall is ill-defined and being set to 0.0 in labels with no true samples. Use `zero_division` parameter to control this behavior.\n",
      "  _warn_prf(average, modifier, msg_start, len(result))\n",
      "/home/pruthvish/JRF/RoadNetwork/RoadNetwork_VirtualEnv/lib/python3.8/site-packages/sklearn/metrics/_classification.py:1599: UndefinedMetricWarning: F-score is ill-defined and being set to 0.0 in labels with no true nor predicted samples. Use `zero_division` parameter to control this behavior.\n",
      "  _warn_prf(average, \"true nor predicted\", \"F-score is\", len(true_sum))\n",
      "/home/pruthvish/JRF/RoadNetwork/RoadNetwork_VirtualEnv/lib/python3.8/site-packages/sklearn/metrics/_classification.py:1334: UndefinedMetricWarning: Precision is ill-defined and being set to 0.0 in labels with no predicted samples. Use `zero_division` parameter to control this behavior.\n",
      "  _warn_prf(average, modifier, msg_start, len(result))\n",
      "/home/pruthvish/JRF/RoadNetwork/RoadNetwork_VirtualEnv/lib/python3.8/site-packages/sklearn/metrics/_classification.py:1334: UndefinedMetricWarning: Recall is ill-defined and being set to 0.0 in labels with no true samples. Use `zero_division` parameter to control this behavior.\n",
      "  _warn_prf(average, modifier, msg_start, len(result))\n",
      "/home/pruthvish/JRF/RoadNetwork/RoadNetwork_VirtualEnv/lib/python3.8/site-packages/sklearn/metrics/_classification.py:1599: UndefinedMetricWarning: F-score is ill-defined and being set to 0.0 in labels with no true nor predicted samples. Use `zero_division` parameter to control this behavior.\n",
      "  _warn_prf(average, \"true nor predicted\", \"F-score is\", len(true_sum))\n",
      "/home/pruthvish/JRF/RoadNetwork/RoadNetwork_VirtualEnv/lib/python3.8/site-packages/sklearn/metrics/_classification.py:1334: UndefinedMetricWarning: Precision is ill-defined and being set to 0.0 in labels with no predicted samples. Use `zero_division` parameter to control this behavior.\n",
      "  _warn_prf(average, modifier, msg_start, len(result))\n",
      "/home/pruthvish/JRF/RoadNetwork/RoadNetwork_VirtualEnv/lib/python3.8/site-packages/sklearn/metrics/_classification.py:1334: UndefinedMetricWarning: Recall is ill-defined and being set to 0.0 in labels with no true samples. Use `zero_division` parameter to control this behavior.\n",
      "  _warn_prf(average, modifier, msg_start, len(result))\n",
      "/home/pruthvish/JRF/RoadNetwork/RoadNetwork_VirtualEnv/lib/python3.8/site-packages/sklearn/metrics/_classification.py:1599: UndefinedMetricWarning: F-score is ill-defined and being set to 0.0 in labels with no true nor predicted samples. Use `zero_division` parameter to control this behavior.\n",
      "  _warn_prf(average, \"true nor predicted\", \"F-score is\", len(true_sum))\n",
      "/home/pruthvish/JRF/RoadNetwork/RoadNetwork_VirtualEnv/lib/python3.8/site-packages/sklearn/metrics/_classification.py:1334: UndefinedMetricWarning: Precision is ill-defined and being set to 0.0 in labels with no predicted samples. Use `zero_division` parameter to control this behavior.\n",
      "  _warn_prf(average, modifier, msg_start, len(result))\n",
      "/home/pruthvish/JRF/RoadNetwork/RoadNetwork_VirtualEnv/lib/python3.8/site-packages/sklearn/metrics/_classification.py:1334: UndefinedMetricWarning: Recall is ill-defined and being set to 0.0 in labels with no true samples. Use `zero_division` parameter to control this behavior.\n",
      "  _warn_prf(average, modifier, msg_start, len(result))\n",
      "/home/pruthvish/JRF/RoadNetwork/RoadNetwork_VirtualEnv/lib/python3.8/site-packages/sklearn/metrics/_classification.py:1599: UndefinedMetricWarning: F-score is ill-defined and being set to 0.0 in labels with no true nor predicted samples. Use `zero_division` parameter to control this behavior.\n",
      "  _warn_prf(average, \"true nor predicted\", \"F-score is\", len(true_sum))\n",
      "/home/pruthvish/JRF/RoadNetwork/RoadNetwork_VirtualEnv/lib/python3.8/site-packages/sklearn/metrics/_classification.py:1334: UndefinedMetricWarning: Precision is ill-defined and being set to 0.0 in labels with no predicted samples. Use `zero_division` parameter to control this behavior.\n",
      "  _warn_prf(average, modifier, msg_start, len(result))\n",
      "/home/pruthvish/JRF/RoadNetwork/RoadNetwork_VirtualEnv/lib/python3.8/site-packages/sklearn/metrics/_classification.py:1334: UndefinedMetricWarning: Recall is ill-defined and being set to 0.0 in labels with no true samples. Use `zero_division` parameter to control this behavior.\n",
      "  _warn_prf(average, modifier, msg_start, len(result))\n",
      "/home/pruthvish/JRF/RoadNetwork/RoadNetwork_VirtualEnv/lib/python3.8/site-packages/sklearn/metrics/_classification.py:1599: UndefinedMetricWarning: F-score is ill-defined and being set to 0.0 in labels with no true nor predicted samples. Use `zero_division` parameter to control this behavior.\n",
      "  _warn_prf(average, \"true nor predicted\", \"F-score is\", len(true_sum))\n",
      "/home/pruthvish/JRF/RoadNetwork/RoadNetwork_VirtualEnv/lib/python3.8/site-packages/sklearn/metrics/_classification.py:1334: UndefinedMetricWarning: Precision is ill-defined and being set to 0.0 in labels with no predicted samples. Use `zero_division` parameter to control this behavior.\n",
      "  _warn_prf(average, modifier, msg_start, len(result))\n",
      "/home/pruthvish/JRF/RoadNetwork/RoadNetwork_VirtualEnv/lib/python3.8/site-packages/sklearn/metrics/_classification.py:1334: UndefinedMetricWarning: Recall is ill-defined and being set to 0.0 in labels with no true samples. Use `zero_division` parameter to control this behavior.\n",
      "  _warn_prf(average, modifier, msg_start, len(result))\n",
      "/home/pruthvish/JRF/RoadNetwork/RoadNetwork_VirtualEnv/lib/python3.8/site-packages/sklearn/metrics/_classification.py:1599: UndefinedMetricWarning: F-score is ill-defined and being set to 0.0 in labels with no true nor predicted samples. Use `zero_division` parameter to control this behavior.\n",
      "  _warn_prf(average, \"true nor predicted\", \"F-score is\", len(true_sum))\n",
      "/home/pruthvish/JRF/RoadNetwork/RoadNetwork_VirtualEnv/lib/python3.8/site-packages/sklearn/metrics/_classification.py:1334: UndefinedMetricWarning: Precision is ill-defined and being set to 0.0 in labels with no predicted samples. Use `zero_division` parameter to control this behavior.\n",
      "  _warn_prf(average, modifier, msg_start, len(result))\n",
      "/home/pruthvish/JRF/RoadNetwork/RoadNetwork_VirtualEnv/lib/python3.8/site-packages/sklearn/metrics/_classification.py:1334: UndefinedMetricWarning: Recall is ill-defined and being set to 0.0 in labels with no true samples. Use `zero_division` parameter to control this behavior.\n",
      "  _warn_prf(average, modifier, msg_start, len(result))\n",
      "/home/pruthvish/JRF/RoadNetwork/RoadNetwork_VirtualEnv/lib/python3.8/site-packages/sklearn/metrics/_classification.py:1599: UndefinedMetricWarning: F-score is ill-defined and being set to 0.0 in labels with no true nor predicted samples. Use `zero_division` parameter to control this behavior.\n",
      "  _warn_prf(average, \"true nor predicted\", \"F-score is\", len(true_sum))\n"
     ]
    },
    {
     "name": "stderr",
     "output_type": "stream",
     "text": [
      "/home/pruthvish/JRF/RoadNetwork/RoadNetwork_VirtualEnv/lib/python3.8/site-packages/sklearn/metrics/_classification.py:1334: UndefinedMetricWarning: Precision is ill-defined and being set to 0.0 in labels with no predicted samples. Use `zero_division` parameter to control this behavior.\n",
      "  _warn_prf(average, modifier, msg_start, len(result))\n",
      "/home/pruthvish/JRF/RoadNetwork/RoadNetwork_VirtualEnv/lib/python3.8/site-packages/sklearn/metrics/_classification.py:1334: UndefinedMetricWarning: Recall is ill-defined and being set to 0.0 in labels with no true samples. Use `zero_division` parameter to control this behavior.\n",
      "  _warn_prf(average, modifier, msg_start, len(result))\n",
      "/home/pruthvish/JRF/RoadNetwork/RoadNetwork_VirtualEnv/lib/python3.8/site-packages/sklearn/metrics/_classification.py:1599: UndefinedMetricWarning: F-score is ill-defined and being set to 0.0 in labels with no true nor predicted samples. Use `zero_division` parameter to control this behavior.\n",
      "  _warn_prf(average, \"true nor predicted\", \"F-score is\", len(true_sum))\n",
      "/home/pruthvish/JRF/RoadNetwork/RoadNetwork_VirtualEnv/lib/python3.8/site-packages/sklearn/metrics/_classification.py:1334: UndefinedMetricWarning: Precision is ill-defined and being set to 0.0 in labels with no predicted samples. Use `zero_division` parameter to control this behavior.\n",
      "  _warn_prf(average, modifier, msg_start, len(result))\n",
      "/home/pruthvish/JRF/RoadNetwork/RoadNetwork_VirtualEnv/lib/python3.8/site-packages/sklearn/metrics/_classification.py:1334: UndefinedMetricWarning: Recall is ill-defined and being set to 0.0 in labels with no true samples. Use `zero_division` parameter to control this behavior.\n",
      "  _warn_prf(average, modifier, msg_start, len(result))\n",
      "/home/pruthvish/JRF/RoadNetwork/RoadNetwork_VirtualEnv/lib/python3.8/site-packages/sklearn/metrics/_classification.py:1599: UndefinedMetricWarning: F-score is ill-defined and being set to 0.0 in labels with no true nor predicted samples. Use `zero_division` parameter to control this behavior.\n",
      "  _warn_prf(average, \"true nor predicted\", \"F-score is\", len(true_sum))\n"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "Feature set-2\n"
     ]
    },
    {
     "name": "stderr",
     "output_type": "stream",
     "text": [
      "/home/pruthvish/JRF/RoadNetwork/RoadNetwork_VirtualEnv/lib/python3.8/site-packages/sklearn/metrics/_classification.py:1334: UndefinedMetricWarning: Precision is ill-defined and being set to 0.0 in labels with no predicted samples. Use `zero_division` parameter to control this behavior.\n",
      "  _warn_prf(average, modifier, msg_start, len(result))\n",
      "/home/pruthvish/JRF/RoadNetwork/RoadNetwork_VirtualEnv/lib/python3.8/site-packages/sklearn/metrics/_classification.py:1334: UndefinedMetricWarning: Recall is ill-defined and being set to 0.0 in labels with no true samples. Use `zero_division` parameter to control this behavior.\n",
      "  _warn_prf(average, modifier, msg_start, len(result))\n",
      "/home/pruthvish/JRF/RoadNetwork/RoadNetwork_VirtualEnv/lib/python3.8/site-packages/sklearn/metrics/_classification.py:1599: UndefinedMetricWarning: F-score is ill-defined and being set to 0.0 in labels with no true nor predicted samples. Use `zero_division` parameter to control this behavior.\n",
      "  _warn_prf(average, \"true nor predicted\", \"F-score is\", len(true_sum))\n",
      "/home/pruthvish/JRF/RoadNetwork/RoadNetwork_VirtualEnv/lib/python3.8/site-packages/sklearn/metrics/_classification.py:1334: UndefinedMetricWarning: Precision is ill-defined and being set to 0.0 in labels with no predicted samples. Use `zero_division` parameter to control this behavior.\n",
      "  _warn_prf(average, modifier, msg_start, len(result))\n",
      "/home/pruthvish/JRF/RoadNetwork/RoadNetwork_VirtualEnv/lib/python3.8/site-packages/sklearn/metrics/_classification.py:1334: UndefinedMetricWarning: Recall is ill-defined and being set to 0.0 in labels with no true samples. Use `zero_division` parameter to control this behavior.\n",
      "  _warn_prf(average, modifier, msg_start, len(result))\n",
      "/home/pruthvish/JRF/RoadNetwork/RoadNetwork_VirtualEnv/lib/python3.8/site-packages/sklearn/metrics/_classification.py:1599: UndefinedMetricWarning: F-score is ill-defined and being set to 0.0 in labels with no true nor predicted samples. Use `zero_division` parameter to control this behavior.\n",
      "  _warn_prf(average, \"true nor predicted\", \"F-score is\", len(true_sum))\n",
      "/home/pruthvish/JRF/RoadNetwork/RoadNetwork_VirtualEnv/lib/python3.8/site-packages/sklearn/metrics/_classification.py:1334: UndefinedMetricWarning: Precision is ill-defined and being set to 0.0 in labels with no predicted samples. Use `zero_division` parameter to control this behavior.\n",
      "  _warn_prf(average, modifier, msg_start, len(result))\n",
      "/home/pruthvish/JRF/RoadNetwork/RoadNetwork_VirtualEnv/lib/python3.8/site-packages/sklearn/metrics/_classification.py:1334: UndefinedMetricWarning: Recall is ill-defined and being set to 0.0 in labels with no true samples. Use `zero_division` parameter to control this behavior.\n",
      "  _warn_prf(average, modifier, msg_start, len(result))\n",
      "/home/pruthvish/JRF/RoadNetwork/RoadNetwork_VirtualEnv/lib/python3.8/site-packages/sklearn/metrics/_classification.py:1599: UndefinedMetricWarning: F-score is ill-defined and being set to 0.0 in labels with no true nor predicted samples. Use `zero_division` parameter to control this behavior.\n",
      "  _warn_prf(average, \"true nor predicted\", \"F-score is\", len(true_sum))\n",
      "/home/pruthvish/JRF/RoadNetwork/RoadNetwork_VirtualEnv/lib/python3.8/site-packages/sklearn/metrics/_classification.py:1334: UndefinedMetricWarning: Precision is ill-defined and being set to 0.0 in labels with no predicted samples. Use `zero_division` parameter to control this behavior.\n",
      "  _warn_prf(average, modifier, msg_start, len(result))\n",
      "/home/pruthvish/JRF/RoadNetwork/RoadNetwork_VirtualEnv/lib/python3.8/site-packages/sklearn/metrics/_classification.py:1334: UndefinedMetricWarning: Recall is ill-defined and being set to 0.0 in labels with no true samples. Use `zero_division` parameter to control this behavior.\n",
      "  _warn_prf(average, modifier, msg_start, len(result))\n",
      "/home/pruthvish/JRF/RoadNetwork/RoadNetwork_VirtualEnv/lib/python3.8/site-packages/sklearn/metrics/_classification.py:1599: UndefinedMetricWarning: F-score is ill-defined and being set to 0.0 in labels with no true nor predicted samples. Use `zero_division` parameter to control this behavior.\n",
      "  _warn_prf(average, \"true nor predicted\", \"F-score is\", len(true_sum))\n",
      "/home/pruthvish/JRF/RoadNetwork/RoadNetwork_VirtualEnv/lib/python3.8/site-packages/sklearn/metrics/_classification.py:1334: UndefinedMetricWarning: Precision is ill-defined and being set to 0.0 in labels with no predicted samples. Use `zero_division` parameter to control this behavior.\n",
      "  _warn_prf(average, modifier, msg_start, len(result))\n",
      "/home/pruthvish/JRF/RoadNetwork/RoadNetwork_VirtualEnv/lib/python3.8/site-packages/sklearn/metrics/_classification.py:1334: UndefinedMetricWarning: Recall is ill-defined and being set to 0.0 in labels with no true samples. Use `zero_division` parameter to control this behavior.\n",
      "  _warn_prf(average, modifier, msg_start, len(result))\n",
      "/home/pruthvish/JRF/RoadNetwork/RoadNetwork_VirtualEnv/lib/python3.8/site-packages/sklearn/metrics/_classification.py:1599: UndefinedMetricWarning: F-score is ill-defined and being set to 0.0 in labels with no true nor predicted samples. Use `zero_division` parameter to control this behavior.\n",
      "  _warn_prf(average, \"true nor predicted\", \"F-score is\", len(true_sum))\n",
      "/home/pruthvish/JRF/RoadNetwork/RoadNetwork_VirtualEnv/lib/python3.8/site-packages/sklearn/metrics/_classification.py:1334: UndefinedMetricWarning: Precision is ill-defined and being set to 0.0 in labels with no predicted samples. Use `zero_division` parameter to control this behavior.\n",
      "  _warn_prf(average, modifier, msg_start, len(result))\n",
      "/home/pruthvish/JRF/RoadNetwork/RoadNetwork_VirtualEnv/lib/python3.8/site-packages/sklearn/metrics/_classification.py:1334: UndefinedMetricWarning: Recall is ill-defined and being set to 0.0 in labels with no true samples. Use `zero_division` parameter to control this behavior.\n",
      "  _warn_prf(average, modifier, msg_start, len(result))\n",
      "/home/pruthvish/JRF/RoadNetwork/RoadNetwork_VirtualEnv/lib/python3.8/site-packages/sklearn/metrics/_classification.py:1599: UndefinedMetricWarning: F-score is ill-defined and being set to 0.0 in labels with no true nor predicted samples. Use `zero_division` parameter to control this behavior.\n",
      "  _warn_prf(average, \"true nor predicted\", \"F-score is\", len(true_sum))\n",
      "/home/pruthvish/JRF/RoadNetwork/RoadNetwork_VirtualEnv/lib/python3.8/site-packages/sklearn/metrics/_classification.py:1334: UndefinedMetricWarning: Precision is ill-defined and being set to 0.0 in labels with no predicted samples. Use `zero_division` parameter to control this behavior.\n",
      "  _warn_prf(average, modifier, msg_start, len(result))\n",
      "/home/pruthvish/JRF/RoadNetwork/RoadNetwork_VirtualEnv/lib/python3.8/site-packages/sklearn/metrics/_classification.py:1334: UndefinedMetricWarning: Recall is ill-defined and being set to 0.0 in labels with no true samples. Use `zero_division` parameter to control this behavior.\n",
      "  _warn_prf(average, modifier, msg_start, len(result))\n",
      "/home/pruthvish/JRF/RoadNetwork/RoadNetwork_VirtualEnv/lib/python3.8/site-packages/sklearn/metrics/_classification.py:1599: UndefinedMetricWarning: F-score is ill-defined and being set to 0.0 in labels with no true nor predicted samples. Use `zero_division` parameter to control this behavior.\n",
      "  _warn_prf(average, \"true nor predicted\", \"F-score is\", len(true_sum))\n",
      "/home/pruthvish/JRF/RoadNetwork/RoadNetwork_VirtualEnv/lib/python3.8/site-packages/sklearn/metrics/_classification.py:1334: UndefinedMetricWarning: Precision is ill-defined and being set to 0.0 in labels with no predicted samples. Use `zero_division` parameter to control this behavior.\n",
      "  _warn_prf(average, modifier, msg_start, len(result))\n",
      "/home/pruthvish/JRF/RoadNetwork/RoadNetwork_VirtualEnv/lib/python3.8/site-packages/sklearn/metrics/_classification.py:1334: UndefinedMetricWarning: Recall is ill-defined and being set to 0.0 in labels with no true samples. Use `zero_division` parameter to control this behavior.\n",
      "  _warn_prf(average, modifier, msg_start, len(result))\n",
      "/home/pruthvish/JRF/RoadNetwork/RoadNetwork_VirtualEnv/lib/python3.8/site-packages/sklearn/metrics/_classification.py:1599: UndefinedMetricWarning: F-score is ill-defined and being set to 0.0 in labels with no true nor predicted samples. Use `zero_division` parameter to control this behavior.\n",
      "  _warn_prf(average, \"true nor predicted\", \"F-score is\", len(true_sum))\n"
     ]
    },
    {
     "name": "stderr",
     "output_type": "stream",
     "text": [
      "/home/pruthvish/JRF/RoadNetwork/RoadNetwork_VirtualEnv/lib/python3.8/site-packages/sklearn/metrics/_classification.py:1334: UndefinedMetricWarning: Precision is ill-defined and being set to 0.0 in labels with no predicted samples. Use `zero_division` parameter to control this behavior.\n",
      "  _warn_prf(average, modifier, msg_start, len(result))\n",
      "/home/pruthvish/JRF/RoadNetwork/RoadNetwork_VirtualEnv/lib/python3.8/site-packages/sklearn/metrics/_classification.py:1334: UndefinedMetricWarning: Recall is ill-defined and being set to 0.0 in labels with no true samples. Use `zero_division` parameter to control this behavior.\n",
      "  _warn_prf(average, modifier, msg_start, len(result))\n",
      "/home/pruthvish/JRF/RoadNetwork/RoadNetwork_VirtualEnv/lib/python3.8/site-packages/sklearn/metrics/_classification.py:1599: UndefinedMetricWarning: F-score is ill-defined and being set to 0.0 in labels with no true nor predicted samples. Use `zero_division` parameter to control this behavior.\n",
      "  _warn_prf(average, \"true nor predicted\", \"F-score is\", len(true_sum))\n",
      "/home/pruthvish/JRF/RoadNetwork/RoadNetwork_VirtualEnv/lib/python3.8/site-packages/sklearn/metrics/_classification.py:1334: UndefinedMetricWarning: Precision is ill-defined and being set to 0.0 in labels with no predicted samples. Use `zero_division` parameter to control this behavior.\n",
      "  _warn_prf(average, modifier, msg_start, len(result))\n",
      "/home/pruthvish/JRF/RoadNetwork/RoadNetwork_VirtualEnv/lib/python3.8/site-packages/sklearn/metrics/_classification.py:1334: UndefinedMetricWarning: Recall is ill-defined and being set to 0.0 in labels with no true samples. Use `zero_division` parameter to control this behavior.\n",
      "  _warn_prf(average, modifier, msg_start, len(result))\n",
      "/home/pruthvish/JRF/RoadNetwork/RoadNetwork_VirtualEnv/lib/python3.8/site-packages/sklearn/metrics/_classification.py:1599: UndefinedMetricWarning: F-score is ill-defined and being set to 0.0 in labels with no true nor predicted samples. Use `zero_division` parameter to control this behavior.\n",
      "  _warn_prf(average, \"true nor predicted\", \"F-score is\", len(true_sum))\n"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "Feature set-3\n"
     ]
    },
    {
     "name": "stderr",
     "output_type": "stream",
     "text": [
      "/home/pruthvish/JRF/RoadNetwork/RoadNetwork_VirtualEnv/lib/python3.8/site-packages/sklearn/metrics/_classification.py:1334: UndefinedMetricWarning: Precision is ill-defined and being set to 0.0 in labels with no predicted samples. Use `zero_division` parameter to control this behavior.\n",
      "  _warn_prf(average, modifier, msg_start, len(result))\n",
      "/home/pruthvish/JRF/RoadNetwork/RoadNetwork_VirtualEnv/lib/python3.8/site-packages/sklearn/metrics/_classification.py:1334: UndefinedMetricWarning: Recall is ill-defined and being set to 0.0 in labels with no true samples. Use `zero_division` parameter to control this behavior.\n",
      "  _warn_prf(average, modifier, msg_start, len(result))\n",
      "/home/pruthvish/JRF/RoadNetwork/RoadNetwork_VirtualEnv/lib/python3.8/site-packages/sklearn/metrics/_classification.py:1599: UndefinedMetricWarning: F-score is ill-defined and being set to 0.0 in labels with no true nor predicted samples. Use `zero_division` parameter to control this behavior.\n",
      "  _warn_prf(average, \"true nor predicted\", \"F-score is\", len(true_sum))\n",
      "/home/pruthvish/JRF/RoadNetwork/RoadNetwork_VirtualEnv/lib/python3.8/site-packages/sklearn/metrics/_classification.py:1334: UndefinedMetricWarning: Precision is ill-defined and being set to 0.0 in labels with no predicted samples. Use `zero_division` parameter to control this behavior.\n",
      "  _warn_prf(average, modifier, msg_start, len(result))\n",
      "/home/pruthvish/JRF/RoadNetwork/RoadNetwork_VirtualEnv/lib/python3.8/site-packages/sklearn/metrics/_classification.py:1334: UndefinedMetricWarning: Recall is ill-defined and being set to 0.0 in labels with no true samples. Use `zero_division` parameter to control this behavior.\n",
      "  _warn_prf(average, modifier, msg_start, len(result))\n",
      "/home/pruthvish/JRF/RoadNetwork/RoadNetwork_VirtualEnv/lib/python3.8/site-packages/sklearn/metrics/_classification.py:1599: UndefinedMetricWarning: F-score is ill-defined and being set to 0.0 in labels with no true nor predicted samples. Use `zero_division` parameter to control this behavior.\n",
      "  _warn_prf(average, \"true nor predicted\", \"F-score is\", len(true_sum))\n",
      "/home/pruthvish/JRF/RoadNetwork/RoadNetwork_VirtualEnv/lib/python3.8/site-packages/sklearn/metrics/_classification.py:1334: UndefinedMetricWarning: Precision is ill-defined and being set to 0.0 in labels with no predicted samples. Use `zero_division` parameter to control this behavior.\n",
      "  _warn_prf(average, modifier, msg_start, len(result))\n",
      "/home/pruthvish/JRF/RoadNetwork/RoadNetwork_VirtualEnv/lib/python3.8/site-packages/sklearn/metrics/_classification.py:1334: UndefinedMetricWarning: Recall is ill-defined and being set to 0.0 in labels with no true samples. Use `zero_division` parameter to control this behavior.\n",
      "  _warn_prf(average, modifier, msg_start, len(result))\n",
      "/home/pruthvish/JRF/RoadNetwork/RoadNetwork_VirtualEnv/lib/python3.8/site-packages/sklearn/metrics/_classification.py:1599: UndefinedMetricWarning: F-score is ill-defined and being set to 0.0 in labels with no true nor predicted samples. Use `zero_division` parameter to control this behavior.\n",
      "  _warn_prf(average, \"true nor predicted\", \"F-score is\", len(true_sum))\n",
      "/home/pruthvish/JRF/RoadNetwork/RoadNetwork_VirtualEnv/lib/python3.8/site-packages/sklearn/metrics/_classification.py:1334: UndefinedMetricWarning: Precision is ill-defined and being set to 0.0 in labels with no predicted samples. Use `zero_division` parameter to control this behavior.\n",
      "  _warn_prf(average, modifier, msg_start, len(result))\n",
      "/home/pruthvish/JRF/RoadNetwork/RoadNetwork_VirtualEnv/lib/python3.8/site-packages/sklearn/metrics/_classification.py:1334: UndefinedMetricWarning: Recall is ill-defined and being set to 0.0 in labels with no true samples. Use `zero_division` parameter to control this behavior.\n",
      "  _warn_prf(average, modifier, msg_start, len(result))\n",
      "/home/pruthvish/JRF/RoadNetwork/RoadNetwork_VirtualEnv/lib/python3.8/site-packages/sklearn/metrics/_classification.py:1599: UndefinedMetricWarning: F-score is ill-defined and being set to 0.0 in labels with no true nor predicted samples. Use `zero_division` parameter to control this behavior.\n",
      "  _warn_prf(average, \"true nor predicted\", \"F-score is\", len(true_sum))\n",
      "/home/pruthvish/JRF/RoadNetwork/RoadNetwork_VirtualEnv/lib/python3.8/site-packages/sklearn/metrics/_classification.py:1334: UndefinedMetricWarning: Precision is ill-defined and being set to 0.0 in labels with no predicted samples. Use `zero_division` parameter to control this behavior.\n",
      "  _warn_prf(average, modifier, msg_start, len(result))\n",
      "/home/pruthvish/JRF/RoadNetwork/RoadNetwork_VirtualEnv/lib/python3.8/site-packages/sklearn/metrics/_classification.py:1334: UndefinedMetricWarning: Recall is ill-defined and being set to 0.0 in labels with no true samples. Use `zero_division` parameter to control this behavior.\n",
      "  _warn_prf(average, modifier, msg_start, len(result))\n",
      "/home/pruthvish/JRF/RoadNetwork/RoadNetwork_VirtualEnv/lib/python3.8/site-packages/sklearn/metrics/_classification.py:1599: UndefinedMetricWarning: F-score is ill-defined and being set to 0.0 in labels with no true nor predicted samples. Use `zero_division` parameter to control this behavior.\n",
      "  _warn_prf(average, \"true nor predicted\", \"F-score is\", len(true_sum))\n",
      "/home/pruthvish/JRF/RoadNetwork/RoadNetwork_VirtualEnv/lib/python3.8/site-packages/sklearn/metrics/_classification.py:1334: UndefinedMetricWarning: Precision is ill-defined and being set to 0.0 in labels with no predicted samples. Use `zero_division` parameter to control this behavior.\n",
      "  _warn_prf(average, modifier, msg_start, len(result))\n",
      "/home/pruthvish/JRF/RoadNetwork/RoadNetwork_VirtualEnv/lib/python3.8/site-packages/sklearn/metrics/_classification.py:1334: UndefinedMetricWarning: Recall is ill-defined and being set to 0.0 in labels with no true samples. Use `zero_division` parameter to control this behavior.\n",
      "  _warn_prf(average, modifier, msg_start, len(result))\n",
      "/home/pruthvish/JRF/RoadNetwork/RoadNetwork_VirtualEnv/lib/python3.8/site-packages/sklearn/metrics/_classification.py:1599: UndefinedMetricWarning: F-score is ill-defined and being set to 0.0 in labels with no true nor predicted samples. Use `zero_division` parameter to control this behavior.\n",
      "  _warn_prf(average, \"true nor predicted\", \"F-score is\", len(true_sum))\n",
      "/home/pruthvish/JRF/RoadNetwork/RoadNetwork_VirtualEnv/lib/python3.8/site-packages/sklearn/metrics/_classification.py:1334: UndefinedMetricWarning: Precision is ill-defined and being set to 0.0 in labels with no predicted samples. Use `zero_division` parameter to control this behavior.\n",
      "  _warn_prf(average, modifier, msg_start, len(result))\n",
      "/home/pruthvish/JRF/RoadNetwork/RoadNetwork_VirtualEnv/lib/python3.8/site-packages/sklearn/metrics/_classification.py:1334: UndefinedMetricWarning: Recall is ill-defined and being set to 0.0 in labels with no true samples. Use `zero_division` parameter to control this behavior.\n",
      "  _warn_prf(average, modifier, msg_start, len(result))\n",
      "/home/pruthvish/JRF/RoadNetwork/RoadNetwork_VirtualEnv/lib/python3.8/site-packages/sklearn/metrics/_classification.py:1599: UndefinedMetricWarning: F-score is ill-defined and being set to 0.0 in labels with no true nor predicted samples. Use `zero_division` parameter to control this behavior.\n",
      "  _warn_prf(average, \"true nor predicted\", \"F-score is\", len(true_sum))\n",
      "/home/pruthvish/JRF/RoadNetwork/RoadNetwork_VirtualEnv/lib/python3.8/site-packages/sklearn/metrics/_classification.py:1334: UndefinedMetricWarning: Precision is ill-defined and being set to 0.0 in labels with no predicted samples. Use `zero_division` parameter to control this behavior.\n",
      "  _warn_prf(average, modifier, msg_start, len(result))\n",
      "/home/pruthvish/JRF/RoadNetwork/RoadNetwork_VirtualEnv/lib/python3.8/site-packages/sklearn/metrics/_classification.py:1334: UndefinedMetricWarning: Recall is ill-defined and being set to 0.0 in labels with no true samples. Use `zero_division` parameter to control this behavior.\n",
      "  _warn_prf(average, modifier, msg_start, len(result))\n",
      "/home/pruthvish/JRF/RoadNetwork/RoadNetwork_VirtualEnv/lib/python3.8/site-packages/sklearn/metrics/_classification.py:1599: UndefinedMetricWarning: F-score is ill-defined and being set to 0.0 in labels with no true nor predicted samples. Use `zero_division` parameter to control this behavior.\n",
      "  _warn_prf(average, \"true nor predicted\", \"F-score is\", len(true_sum))\n"
     ]
    },
    {
     "name": "stderr",
     "output_type": "stream",
     "text": [
      "/home/pruthvish/JRF/RoadNetwork/RoadNetwork_VirtualEnv/lib/python3.8/site-packages/sklearn/metrics/_classification.py:1334: UndefinedMetricWarning: Precision is ill-defined and being set to 0.0 in labels with no predicted samples. Use `zero_division` parameter to control this behavior.\n",
      "  _warn_prf(average, modifier, msg_start, len(result))\n",
      "/home/pruthvish/JRF/RoadNetwork/RoadNetwork_VirtualEnv/lib/python3.8/site-packages/sklearn/metrics/_classification.py:1334: UndefinedMetricWarning: Recall is ill-defined and being set to 0.0 in labels with no true samples. Use `zero_division` parameter to control this behavior.\n",
      "  _warn_prf(average, modifier, msg_start, len(result))\n",
      "/home/pruthvish/JRF/RoadNetwork/RoadNetwork_VirtualEnv/lib/python3.8/site-packages/sklearn/metrics/_classification.py:1599: UndefinedMetricWarning: F-score is ill-defined and being set to 0.0 in labels with no true nor predicted samples. Use `zero_division` parameter to control this behavior.\n",
      "  _warn_prf(average, \"true nor predicted\", \"F-score is\", len(true_sum))\n",
      "/home/pruthvish/JRF/RoadNetwork/RoadNetwork_VirtualEnv/lib/python3.8/site-packages/sklearn/metrics/_classification.py:1334: UndefinedMetricWarning: Precision is ill-defined and being set to 0.0 in labels with no predicted samples. Use `zero_division` parameter to control this behavior.\n",
      "  _warn_prf(average, modifier, msg_start, len(result))\n",
      "/home/pruthvish/JRF/RoadNetwork/RoadNetwork_VirtualEnv/lib/python3.8/site-packages/sklearn/metrics/_classification.py:1334: UndefinedMetricWarning: Recall is ill-defined and being set to 0.0 in labels with no true samples. Use `zero_division` parameter to control this behavior.\n",
      "  _warn_prf(average, modifier, msg_start, len(result))\n",
      "/home/pruthvish/JRF/RoadNetwork/RoadNetwork_VirtualEnv/lib/python3.8/site-packages/sklearn/metrics/_classification.py:1599: UndefinedMetricWarning: F-score is ill-defined and being set to 0.0 in labels with no true nor predicted samples. Use `zero_division` parameter to control this behavior.\n",
      "  _warn_prf(average, \"true nor predicted\", \"F-score is\", len(true_sum))\n"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "Feature set-4\n"
     ]
    },
    {
     "name": "stderr",
     "output_type": "stream",
     "text": [
      "/home/pruthvish/JRF/RoadNetwork/RoadNetwork_VirtualEnv/lib/python3.8/site-packages/sklearn/metrics/_classification.py:1334: UndefinedMetricWarning: Precision is ill-defined and being set to 0.0 in labels with no predicted samples. Use `zero_division` parameter to control this behavior.\n",
      "  _warn_prf(average, modifier, msg_start, len(result))\n",
      "/home/pruthvish/JRF/RoadNetwork/RoadNetwork_VirtualEnv/lib/python3.8/site-packages/sklearn/metrics/_classification.py:1334: UndefinedMetricWarning: Recall is ill-defined and being set to 0.0 in labels with no true samples. Use `zero_division` parameter to control this behavior.\n",
      "  _warn_prf(average, modifier, msg_start, len(result))\n",
      "/home/pruthvish/JRF/RoadNetwork/RoadNetwork_VirtualEnv/lib/python3.8/site-packages/sklearn/metrics/_classification.py:1599: UndefinedMetricWarning: F-score is ill-defined and being set to 0.0 in labels with no true nor predicted samples. Use `zero_division` parameter to control this behavior.\n",
      "  _warn_prf(average, \"true nor predicted\", \"F-score is\", len(true_sum))\n",
      "/home/pruthvish/JRF/RoadNetwork/RoadNetwork_VirtualEnv/lib/python3.8/site-packages/sklearn/metrics/_classification.py:1334: UndefinedMetricWarning: Precision is ill-defined and being set to 0.0 in labels with no predicted samples. Use `zero_division` parameter to control this behavior.\n",
      "  _warn_prf(average, modifier, msg_start, len(result))\n",
      "/home/pruthvish/JRF/RoadNetwork/RoadNetwork_VirtualEnv/lib/python3.8/site-packages/sklearn/metrics/_classification.py:1334: UndefinedMetricWarning: Recall is ill-defined and being set to 0.0 in labels with no true samples. Use `zero_division` parameter to control this behavior.\n",
      "  _warn_prf(average, modifier, msg_start, len(result))\n",
      "/home/pruthvish/JRF/RoadNetwork/RoadNetwork_VirtualEnv/lib/python3.8/site-packages/sklearn/metrics/_classification.py:1599: UndefinedMetricWarning: F-score is ill-defined and being set to 0.0 in labels with no true nor predicted samples. Use `zero_division` parameter to control this behavior.\n",
      "  _warn_prf(average, \"true nor predicted\", \"F-score is\", len(true_sum))\n",
      "/home/pruthvish/JRF/RoadNetwork/RoadNetwork_VirtualEnv/lib/python3.8/site-packages/sklearn/metrics/_classification.py:1334: UndefinedMetricWarning: Precision is ill-defined and being set to 0.0 in labels with no predicted samples. Use `zero_division` parameter to control this behavior.\n",
      "  _warn_prf(average, modifier, msg_start, len(result))\n",
      "/home/pruthvish/JRF/RoadNetwork/RoadNetwork_VirtualEnv/lib/python3.8/site-packages/sklearn/metrics/_classification.py:1334: UndefinedMetricWarning: Recall is ill-defined and being set to 0.0 in labels with no true samples. Use `zero_division` parameter to control this behavior.\n",
      "  _warn_prf(average, modifier, msg_start, len(result))\n",
      "/home/pruthvish/JRF/RoadNetwork/RoadNetwork_VirtualEnv/lib/python3.8/site-packages/sklearn/metrics/_classification.py:1599: UndefinedMetricWarning: F-score is ill-defined and being set to 0.0 in labels with no true nor predicted samples. Use `zero_division` parameter to control this behavior.\n",
      "  _warn_prf(average, \"true nor predicted\", \"F-score is\", len(true_sum))\n",
      "/home/pruthvish/JRF/RoadNetwork/RoadNetwork_VirtualEnv/lib/python3.8/site-packages/sklearn/metrics/_classification.py:1334: UndefinedMetricWarning: Precision is ill-defined and being set to 0.0 in labels with no predicted samples. Use `zero_division` parameter to control this behavior.\n",
      "  _warn_prf(average, modifier, msg_start, len(result))\n",
      "/home/pruthvish/JRF/RoadNetwork/RoadNetwork_VirtualEnv/lib/python3.8/site-packages/sklearn/metrics/_classification.py:1334: UndefinedMetricWarning: Recall is ill-defined and being set to 0.0 in labels with no true samples. Use `zero_division` parameter to control this behavior.\n",
      "  _warn_prf(average, modifier, msg_start, len(result))\n",
      "/home/pruthvish/JRF/RoadNetwork/RoadNetwork_VirtualEnv/lib/python3.8/site-packages/sklearn/metrics/_classification.py:1599: UndefinedMetricWarning: F-score is ill-defined and being set to 0.0 in labels with no true nor predicted samples. Use `zero_division` parameter to control this behavior.\n",
      "  _warn_prf(average, \"true nor predicted\", \"F-score is\", len(true_sum))\n",
      "/home/pruthvish/JRF/RoadNetwork/RoadNetwork_VirtualEnv/lib/python3.8/site-packages/sklearn/metrics/_classification.py:1334: UndefinedMetricWarning: Precision is ill-defined and being set to 0.0 in labels with no predicted samples. Use `zero_division` parameter to control this behavior.\n",
      "  _warn_prf(average, modifier, msg_start, len(result))\n",
      "/home/pruthvish/JRF/RoadNetwork/RoadNetwork_VirtualEnv/lib/python3.8/site-packages/sklearn/metrics/_classification.py:1334: UndefinedMetricWarning: Recall is ill-defined and being set to 0.0 in labels with no true samples. Use `zero_division` parameter to control this behavior.\n",
      "  _warn_prf(average, modifier, msg_start, len(result))\n",
      "/home/pruthvish/JRF/RoadNetwork/RoadNetwork_VirtualEnv/lib/python3.8/site-packages/sklearn/metrics/_classification.py:1599: UndefinedMetricWarning: F-score is ill-defined and being set to 0.0 in labels with no true nor predicted samples. Use `zero_division` parameter to control this behavior.\n",
      "  _warn_prf(average, \"true nor predicted\", \"F-score is\", len(true_sum))\n",
      "/home/pruthvish/JRF/RoadNetwork/RoadNetwork_VirtualEnv/lib/python3.8/site-packages/sklearn/metrics/_classification.py:1334: UndefinedMetricWarning: Precision is ill-defined and being set to 0.0 in labels with no predicted samples. Use `zero_division` parameter to control this behavior.\n",
      "  _warn_prf(average, modifier, msg_start, len(result))\n",
      "/home/pruthvish/JRF/RoadNetwork/RoadNetwork_VirtualEnv/lib/python3.8/site-packages/sklearn/metrics/_classification.py:1334: UndefinedMetricWarning: Recall is ill-defined and being set to 0.0 in labels with no true samples. Use `zero_division` parameter to control this behavior.\n",
      "  _warn_prf(average, modifier, msg_start, len(result))\n",
      "/home/pruthvish/JRF/RoadNetwork/RoadNetwork_VirtualEnv/lib/python3.8/site-packages/sklearn/metrics/_classification.py:1599: UndefinedMetricWarning: F-score is ill-defined and being set to 0.0 in labels with no true nor predicted samples. Use `zero_division` parameter to control this behavior.\n",
      "  _warn_prf(average, \"true nor predicted\", \"F-score is\", len(true_sum))\n",
      "/home/pruthvish/JRF/RoadNetwork/RoadNetwork_VirtualEnv/lib/python3.8/site-packages/sklearn/metrics/_classification.py:1334: UndefinedMetricWarning: Precision is ill-defined and being set to 0.0 in labels with no predicted samples. Use `zero_division` parameter to control this behavior.\n",
      "  _warn_prf(average, modifier, msg_start, len(result))\n",
      "/home/pruthvish/JRF/RoadNetwork/RoadNetwork_VirtualEnv/lib/python3.8/site-packages/sklearn/metrics/_classification.py:1334: UndefinedMetricWarning: Recall is ill-defined and being set to 0.0 in labels with no true samples. Use `zero_division` parameter to control this behavior.\n",
      "  _warn_prf(average, modifier, msg_start, len(result))\n",
      "/home/pruthvish/JRF/RoadNetwork/RoadNetwork_VirtualEnv/lib/python3.8/site-packages/sklearn/metrics/_classification.py:1599: UndefinedMetricWarning: F-score is ill-defined and being set to 0.0 in labels with no true nor predicted samples. Use `zero_division` parameter to control this behavior.\n",
      "  _warn_prf(average, \"true nor predicted\", \"F-score is\", len(true_sum))\n",
      "/home/pruthvish/JRF/RoadNetwork/RoadNetwork_VirtualEnv/lib/python3.8/site-packages/sklearn/metrics/_classification.py:1334: UndefinedMetricWarning: Precision is ill-defined and being set to 0.0 in labels with no predicted samples. Use `zero_division` parameter to control this behavior.\n",
      "  _warn_prf(average, modifier, msg_start, len(result))\n",
      "/home/pruthvish/JRF/RoadNetwork/RoadNetwork_VirtualEnv/lib/python3.8/site-packages/sklearn/metrics/_classification.py:1334: UndefinedMetricWarning: Recall is ill-defined and being set to 0.0 in labels with no true samples. Use `zero_division` parameter to control this behavior.\n",
      "  _warn_prf(average, modifier, msg_start, len(result))\n",
      "/home/pruthvish/JRF/RoadNetwork/RoadNetwork_VirtualEnv/lib/python3.8/site-packages/sklearn/metrics/_classification.py:1599: UndefinedMetricWarning: F-score is ill-defined and being set to 0.0 in labels with no true nor predicted samples. Use `zero_division` parameter to control this behavior.\n",
      "  _warn_prf(average, \"true nor predicted\", \"F-score is\", len(true_sum))\n"
     ]
    },
    {
     "name": "stderr",
     "output_type": "stream",
     "text": [
      "/home/pruthvish/JRF/RoadNetwork/RoadNetwork_VirtualEnv/lib/python3.8/site-packages/sklearn/metrics/_classification.py:1334: UndefinedMetricWarning: Precision is ill-defined and being set to 0.0 in labels with no predicted samples. Use `zero_division` parameter to control this behavior.\n",
      "  _warn_prf(average, modifier, msg_start, len(result))\n",
      "/home/pruthvish/JRF/RoadNetwork/RoadNetwork_VirtualEnv/lib/python3.8/site-packages/sklearn/metrics/_classification.py:1334: UndefinedMetricWarning: Recall is ill-defined and being set to 0.0 in labels with no true samples. Use `zero_division` parameter to control this behavior.\n",
      "  _warn_prf(average, modifier, msg_start, len(result))\n",
      "/home/pruthvish/JRF/RoadNetwork/RoadNetwork_VirtualEnv/lib/python3.8/site-packages/sklearn/metrics/_classification.py:1599: UndefinedMetricWarning: F-score is ill-defined and being set to 0.0 in labels with no true nor predicted samples. Use `zero_division` parameter to control this behavior.\n",
      "  _warn_prf(average, \"true nor predicted\", \"F-score is\", len(true_sum))\n",
      "/home/pruthvish/JRF/RoadNetwork/RoadNetwork_VirtualEnv/lib/python3.8/site-packages/sklearn/metrics/_classification.py:1334: UndefinedMetricWarning: Precision is ill-defined and being set to 0.0 in labels with no predicted samples. Use `zero_division` parameter to control this behavior.\n",
      "  _warn_prf(average, modifier, msg_start, len(result))\n",
      "/home/pruthvish/JRF/RoadNetwork/RoadNetwork_VirtualEnv/lib/python3.8/site-packages/sklearn/metrics/_classification.py:1334: UndefinedMetricWarning: Recall is ill-defined and being set to 0.0 in labels with no true samples. Use `zero_division` parameter to control this behavior.\n",
      "  _warn_prf(average, modifier, msg_start, len(result))\n",
      "/home/pruthvish/JRF/RoadNetwork/RoadNetwork_VirtualEnv/lib/python3.8/site-packages/sklearn/metrics/_classification.py:1599: UndefinedMetricWarning: F-score is ill-defined and being set to 0.0 in labels with no true nor predicted samples. Use `zero_division` parameter to control this behavior.\n",
      "  _warn_prf(average, \"true nor predicted\", \"F-score is\", len(true_sum))\n"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "Classifier, ClassifierName DecisionTreeClassifier() DT\n",
      "Feature set-1\n"
     ]
    },
    {
     "name": "stderr",
     "output_type": "stream",
     "text": [
      "/home/pruthvish/JRF/RoadNetwork/RoadNetwork_VirtualEnv/lib/python3.8/site-packages/sklearn/metrics/_classification.py:1334: UndefinedMetricWarning: Precision is ill-defined and being set to 0.0 in labels with no predicted samples. Use `zero_division` parameter to control this behavior.\n",
      "  _warn_prf(average, modifier, msg_start, len(result))\n",
      "/home/pruthvish/JRF/RoadNetwork/RoadNetwork_VirtualEnv/lib/python3.8/site-packages/sklearn/metrics/_classification.py:1334: UndefinedMetricWarning: Recall is ill-defined and being set to 0.0 in labels with no true samples. Use `zero_division` parameter to control this behavior.\n",
      "  _warn_prf(average, modifier, msg_start, len(result))\n",
      "/home/pruthvish/JRF/RoadNetwork/RoadNetwork_VirtualEnv/lib/python3.8/site-packages/sklearn/metrics/_classification.py:1599: UndefinedMetricWarning: F-score is ill-defined and being set to 0.0 in labels with no true nor predicted samples. Use `zero_division` parameter to control this behavior.\n",
      "  _warn_prf(average, \"true nor predicted\", \"F-score is\", len(true_sum))\n",
      "/home/pruthvish/JRF/RoadNetwork/RoadNetwork_VirtualEnv/lib/python3.8/site-packages/sklearn/metrics/_classification.py:1334: UndefinedMetricWarning: Precision is ill-defined and being set to 0.0 in labels with no predicted samples. Use `zero_division` parameter to control this behavior.\n",
      "  _warn_prf(average, modifier, msg_start, len(result))\n",
      "/home/pruthvish/JRF/RoadNetwork/RoadNetwork_VirtualEnv/lib/python3.8/site-packages/sklearn/metrics/_classification.py:1334: UndefinedMetricWarning: Recall is ill-defined and being set to 0.0 in labels with no true samples. Use `zero_division` parameter to control this behavior.\n",
      "  _warn_prf(average, modifier, msg_start, len(result))\n",
      "/home/pruthvish/JRF/RoadNetwork/RoadNetwork_VirtualEnv/lib/python3.8/site-packages/sklearn/metrics/_classification.py:1599: UndefinedMetricWarning: F-score is ill-defined and being set to 0.0 in labels with no true nor predicted samples. Use `zero_division` parameter to control this behavior.\n",
      "  _warn_prf(average, \"true nor predicted\", \"F-score is\", len(true_sum))\n",
      "/home/pruthvish/JRF/RoadNetwork/RoadNetwork_VirtualEnv/lib/python3.8/site-packages/sklearn/metrics/_classification.py:1334: UndefinedMetricWarning: Precision is ill-defined and being set to 0.0 in labels with no predicted samples. Use `zero_division` parameter to control this behavior.\n",
      "  _warn_prf(average, modifier, msg_start, len(result))\n",
      "/home/pruthvish/JRF/RoadNetwork/RoadNetwork_VirtualEnv/lib/python3.8/site-packages/sklearn/metrics/_classification.py:1334: UndefinedMetricWarning: Recall is ill-defined and being set to 0.0 in labels with no true samples. Use `zero_division` parameter to control this behavior.\n",
      "  _warn_prf(average, modifier, msg_start, len(result))\n",
      "/home/pruthvish/JRF/RoadNetwork/RoadNetwork_VirtualEnv/lib/python3.8/site-packages/sklearn/metrics/_classification.py:1599: UndefinedMetricWarning: F-score is ill-defined and being set to 0.0 in labels with no true nor predicted samples. Use `zero_division` parameter to control this behavior.\n",
      "  _warn_prf(average, \"true nor predicted\", \"F-score is\", len(true_sum))\n",
      "/home/pruthvish/JRF/RoadNetwork/RoadNetwork_VirtualEnv/lib/python3.8/site-packages/sklearn/metrics/_classification.py:1334: UndefinedMetricWarning: Precision is ill-defined and being set to 0.0 in labels with no predicted samples. Use `zero_division` parameter to control this behavior.\n",
      "  _warn_prf(average, modifier, msg_start, len(result))\n",
      "/home/pruthvish/JRF/RoadNetwork/RoadNetwork_VirtualEnv/lib/python3.8/site-packages/sklearn/metrics/_classification.py:1334: UndefinedMetricWarning: Recall is ill-defined and being set to 0.0 in labels with no true samples. Use `zero_division` parameter to control this behavior.\n",
      "  _warn_prf(average, modifier, msg_start, len(result))\n",
      "/home/pruthvish/JRF/RoadNetwork/RoadNetwork_VirtualEnv/lib/python3.8/site-packages/sklearn/metrics/_classification.py:1599: UndefinedMetricWarning: F-score is ill-defined and being set to 0.0 in labels with no true nor predicted samples. Use `zero_division` parameter to control this behavior.\n",
      "  _warn_prf(average, \"true nor predicted\", \"F-score is\", len(true_sum))\n",
      "/home/pruthvish/JRF/RoadNetwork/RoadNetwork_VirtualEnv/lib/python3.8/site-packages/sklearn/metrics/_classification.py:1334: UndefinedMetricWarning: Precision is ill-defined and being set to 0.0 in labels with no predicted samples. Use `zero_division` parameter to control this behavior.\n",
      "  _warn_prf(average, modifier, msg_start, len(result))\n",
      "/home/pruthvish/JRF/RoadNetwork/RoadNetwork_VirtualEnv/lib/python3.8/site-packages/sklearn/metrics/_classification.py:1334: UndefinedMetricWarning: Recall is ill-defined and being set to 0.0 in labels with no true samples. Use `zero_division` parameter to control this behavior.\n",
      "  _warn_prf(average, modifier, msg_start, len(result))\n",
      "/home/pruthvish/JRF/RoadNetwork/RoadNetwork_VirtualEnv/lib/python3.8/site-packages/sklearn/metrics/_classification.py:1599: UndefinedMetricWarning: F-score is ill-defined and being set to 0.0 in labels with no true nor predicted samples. Use `zero_division` parameter to control this behavior.\n",
      "  _warn_prf(average, \"true nor predicted\", \"F-score is\", len(true_sum))\n",
      "/home/pruthvish/JRF/RoadNetwork/RoadNetwork_VirtualEnv/lib/python3.8/site-packages/sklearn/metrics/_classification.py:1334: UndefinedMetricWarning: Precision is ill-defined and being set to 0.0 in labels with no predicted samples. Use `zero_division` parameter to control this behavior.\n",
      "  _warn_prf(average, modifier, msg_start, len(result))\n",
      "/home/pruthvish/JRF/RoadNetwork/RoadNetwork_VirtualEnv/lib/python3.8/site-packages/sklearn/metrics/_classification.py:1334: UndefinedMetricWarning: Recall is ill-defined and being set to 0.0 in labels with no true samples. Use `zero_division` parameter to control this behavior.\n",
      "  _warn_prf(average, modifier, msg_start, len(result))\n",
      "/home/pruthvish/JRF/RoadNetwork/RoadNetwork_VirtualEnv/lib/python3.8/site-packages/sklearn/metrics/_classification.py:1599: UndefinedMetricWarning: F-score is ill-defined and being set to 0.0 in labels with no true nor predicted samples. Use `zero_division` parameter to control this behavior.\n",
      "  _warn_prf(average, \"true nor predicted\", \"F-score is\", len(true_sum))\n",
      "/home/pruthvish/JRF/RoadNetwork/RoadNetwork_VirtualEnv/lib/python3.8/site-packages/sklearn/metrics/_classification.py:1334: UndefinedMetricWarning: Precision is ill-defined and being set to 0.0 in labels with no predicted samples. Use `zero_division` parameter to control this behavior.\n",
      "  _warn_prf(average, modifier, msg_start, len(result))\n",
      "/home/pruthvish/JRF/RoadNetwork/RoadNetwork_VirtualEnv/lib/python3.8/site-packages/sklearn/metrics/_classification.py:1334: UndefinedMetricWarning: Recall is ill-defined and being set to 0.0 in labels with no true samples. Use `zero_division` parameter to control this behavior.\n",
      "  _warn_prf(average, modifier, msg_start, len(result))\n",
      "/home/pruthvish/JRF/RoadNetwork/RoadNetwork_VirtualEnv/lib/python3.8/site-packages/sklearn/metrics/_classification.py:1599: UndefinedMetricWarning: F-score is ill-defined and being set to 0.0 in labels with no true nor predicted samples. Use `zero_division` parameter to control this behavior.\n",
      "  _warn_prf(average, \"true nor predicted\", \"F-score is\", len(true_sum))\n",
      "/home/pruthvish/JRF/RoadNetwork/RoadNetwork_VirtualEnv/lib/python3.8/site-packages/sklearn/metrics/_classification.py:1334: UndefinedMetricWarning: Precision is ill-defined and being set to 0.0 in labels with no predicted samples. Use `zero_division` parameter to control this behavior.\n",
      "  _warn_prf(average, modifier, msg_start, len(result))\n",
      "/home/pruthvish/JRF/RoadNetwork/RoadNetwork_VirtualEnv/lib/python3.8/site-packages/sklearn/metrics/_classification.py:1334: UndefinedMetricWarning: Recall is ill-defined and being set to 0.0 in labels with no true samples. Use `zero_division` parameter to control this behavior.\n",
      "  _warn_prf(average, modifier, msg_start, len(result))\n",
      "/home/pruthvish/JRF/RoadNetwork/RoadNetwork_VirtualEnv/lib/python3.8/site-packages/sklearn/metrics/_classification.py:1599: UndefinedMetricWarning: F-score is ill-defined and being set to 0.0 in labels with no true nor predicted samples. Use `zero_division` parameter to control this behavior.\n",
      "  _warn_prf(average, \"true nor predicted\", \"F-score is\", len(true_sum))\n"
     ]
    },
    {
     "name": "stderr",
     "output_type": "stream",
     "text": [
      "/home/pruthvish/JRF/RoadNetwork/RoadNetwork_VirtualEnv/lib/python3.8/site-packages/sklearn/metrics/_classification.py:1334: UndefinedMetricWarning: Precision is ill-defined and being set to 0.0 in labels with no predicted samples. Use `zero_division` parameter to control this behavior.\n",
      "  _warn_prf(average, modifier, msg_start, len(result))\n",
      "/home/pruthvish/JRF/RoadNetwork/RoadNetwork_VirtualEnv/lib/python3.8/site-packages/sklearn/metrics/_classification.py:1334: UndefinedMetricWarning: Recall is ill-defined and being set to 0.0 in labels with no true samples. Use `zero_division` parameter to control this behavior.\n",
      "  _warn_prf(average, modifier, msg_start, len(result))\n",
      "/home/pruthvish/JRF/RoadNetwork/RoadNetwork_VirtualEnv/lib/python3.8/site-packages/sklearn/metrics/_classification.py:1599: UndefinedMetricWarning: F-score is ill-defined and being set to 0.0 in labels with no true nor predicted samples. Use `zero_division` parameter to control this behavior.\n",
      "  _warn_prf(average, \"true nor predicted\", \"F-score is\", len(true_sum))\n",
      "/home/pruthvish/JRF/RoadNetwork/RoadNetwork_VirtualEnv/lib/python3.8/site-packages/sklearn/metrics/_classification.py:1334: UndefinedMetricWarning: Precision is ill-defined and being set to 0.0 in labels with no predicted samples. Use `zero_division` parameter to control this behavior.\n",
      "  _warn_prf(average, modifier, msg_start, len(result))\n",
      "/home/pruthvish/JRF/RoadNetwork/RoadNetwork_VirtualEnv/lib/python3.8/site-packages/sklearn/metrics/_classification.py:1334: UndefinedMetricWarning: Recall is ill-defined and being set to 0.0 in labels with no true samples. Use `zero_division` parameter to control this behavior.\n",
      "  _warn_prf(average, modifier, msg_start, len(result))\n",
      "/home/pruthvish/JRF/RoadNetwork/RoadNetwork_VirtualEnv/lib/python3.8/site-packages/sklearn/metrics/_classification.py:1599: UndefinedMetricWarning: F-score is ill-defined and being set to 0.0 in labels with no true nor predicted samples. Use `zero_division` parameter to control this behavior.\n",
      "  _warn_prf(average, \"true nor predicted\", \"F-score is\", len(true_sum))\n"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "Feature set-2\n"
     ]
    },
    {
     "name": "stderr",
     "output_type": "stream",
     "text": [
      "/home/pruthvish/JRF/RoadNetwork/RoadNetwork_VirtualEnv/lib/python3.8/site-packages/sklearn/metrics/_classification.py:1334: UndefinedMetricWarning: Precision is ill-defined and being set to 0.0 in labels with no predicted samples. Use `zero_division` parameter to control this behavior.\n",
      "  _warn_prf(average, modifier, msg_start, len(result))\n",
      "/home/pruthvish/JRF/RoadNetwork/RoadNetwork_VirtualEnv/lib/python3.8/site-packages/sklearn/metrics/_classification.py:1334: UndefinedMetricWarning: Recall is ill-defined and being set to 0.0 in labels with no true samples. Use `zero_division` parameter to control this behavior.\n",
      "  _warn_prf(average, modifier, msg_start, len(result))\n",
      "/home/pruthvish/JRF/RoadNetwork/RoadNetwork_VirtualEnv/lib/python3.8/site-packages/sklearn/metrics/_classification.py:1599: UndefinedMetricWarning: F-score is ill-defined and being set to 0.0 in labels with no true nor predicted samples. Use `zero_division` parameter to control this behavior.\n",
      "  _warn_prf(average, \"true nor predicted\", \"F-score is\", len(true_sum))\n",
      "/home/pruthvish/JRF/RoadNetwork/RoadNetwork_VirtualEnv/lib/python3.8/site-packages/sklearn/metrics/_classification.py:1334: UndefinedMetricWarning: Precision is ill-defined and being set to 0.0 in labels with no predicted samples. Use `zero_division` parameter to control this behavior.\n",
      "  _warn_prf(average, modifier, msg_start, len(result))\n",
      "/home/pruthvish/JRF/RoadNetwork/RoadNetwork_VirtualEnv/lib/python3.8/site-packages/sklearn/metrics/_classification.py:1334: UndefinedMetricWarning: Recall is ill-defined and being set to 0.0 in labels with no true samples. Use `zero_division` parameter to control this behavior.\n",
      "  _warn_prf(average, modifier, msg_start, len(result))\n",
      "/home/pruthvish/JRF/RoadNetwork/RoadNetwork_VirtualEnv/lib/python3.8/site-packages/sklearn/metrics/_classification.py:1599: UndefinedMetricWarning: F-score is ill-defined and being set to 0.0 in labels with no true nor predicted samples. Use `zero_division` parameter to control this behavior.\n",
      "  _warn_prf(average, \"true nor predicted\", \"F-score is\", len(true_sum))\n",
      "/home/pruthvish/JRF/RoadNetwork/RoadNetwork_VirtualEnv/lib/python3.8/site-packages/sklearn/metrics/_classification.py:1334: UndefinedMetricWarning: Precision is ill-defined and being set to 0.0 in labels with no predicted samples. Use `zero_division` parameter to control this behavior.\n",
      "  _warn_prf(average, modifier, msg_start, len(result))\n",
      "/home/pruthvish/JRF/RoadNetwork/RoadNetwork_VirtualEnv/lib/python3.8/site-packages/sklearn/metrics/_classification.py:1334: UndefinedMetricWarning: Recall is ill-defined and being set to 0.0 in labels with no true samples. Use `zero_division` parameter to control this behavior.\n",
      "  _warn_prf(average, modifier, msg_start, len(result))\n",
      "/home/pruthvish/JRF/RoadNetwork/RoadNetwork_VirtualEnv/lib/python3.8/site-packages/sklearn/metrics/_classification.py:1599: UndefinedMetricWarning: F-score is ill-defined and being set to 0.0 in labels with no true nor predicted samples. Use `zero_division` parameter to control this behavior.\n",
      "  _warn_prf(average, \"true nor predicted\", \"F-score is\", len(true_sum))\n",
      "/home/pruthvish/JRF/RoadNetwork/RoadNetwork_VirtualEnv/lib/python3.8/site-packages/sklearn/metrics/_classification.py:1334: UndefinedMetricWarning: Precision is ill-defined and being set to 0.0 in labels with no predicted samples. Use `zero_division` parameter to control this behavior.\n",
      "  _warn_prf(average, modifier, msg_start, len(result))\n",
      "/home/pruthvish/JRF/RoadNetwork/RoadNetwork_VirtualEnv/lib/python3.8/site-packages/sklearn/metrics/_classification.py:1334: UndefinedMetricWarning: Recall is ill-defined and being set to 0.0 in labels with no true samples. Use `zero_division` parameter to control this behavior.\n",
      "  _warn_prf(average, modifier, msg_start, len(result))\n",
      "/home/pruthvish/JRF/RoadNetwork/RoadNetwork_VirtualEnv/lib/python3.8/site-packages/sklearn/metrics/_classification.py:1599: UndefinedMetricWarning: F-score is ill-defined and being set to 0.0 in labels with no true nor predicted samples. Use `zero_division` parameter to control this behavior.\n",
      "  _warn_prf(average, \"true nor predicted\", \"F-score is\", len(true_sum))\n",
      "/home/pruthvish/JRF/RoadNetwork/RoadNetwork_VirtualEnv/lib/python3.8/site-packages/sklearn/metrics/_classification.py:1334: UndefinedMetricWarning: Precision is ill-defined and being set to 0.0 in labels with no predicted samples. Use `zero_division` parameter to control this behavior.\n",
      "  _warn_prf(average, modifier, msg_start, len(result))\n",
      "/home/pruthvish/JRF/RoadNetwork/RoadNetwork_VirtualEnv/lib/python3.8/site-packages/sklearn/metrics/_classification.py:1334: UndefinedMetricWarning: Recall is ill-defined and being set to 0.0 in labels with no true samples. Use `zero_division` parameter to control this behavior.\n",
      "  _warn_prf(average, modifier, msg_start, len(result))\n",
      "/home/pruthvish/JRF/RoadNetwork/RoadNetwork_VirtualEnv/lib/python3.8/site-packages/sklearn/metrics/_classification.py:1599: UndefinedMetricWarning: F-score is ill-defined and being set to 0.0 in labels with no true nor predicted samples. Use `zero_division` parameter to control this behavior.\n",
      "  _warn_prf(average, \"true nor predicted\", \"F-score is\", len(true_sum))\n",
      "/home/pruthvish/JRF/RoadNetwork/RoadNetwork_VirtualEnv/lib/python3.8/site-packages/sklearn/metrics/_classification.py:1334: UndefinedMetricWarning: Precision is ill-defined and being set to 0.0 in labels with no predicted samples. Use `zero_division` parameter to control this behavior.\n",
      "  _warn_prf(average, modifier, msg_start, len(result))\n",
      "/home/pruthvish/JRF/RoadNetwork/RoadNetwork_VirtualEnv/lib/python3.8/site-packages/sklearn/metrics/_classification.py:1334: UndefinedMetricWarning: Recall is ill-defined and being set to 0.0 in labels with no true samples. Use `zero_division` parameter to control this behavior.\n",
      "  _warn_prf(average, modifier, msg_start, len(result))\n",
      "/home/pruthvish/JRF/RoadNetwork/RoadNetwork_VirtualEnv/lib/python3.8/site-packages/sklearn/metrics/_classification.py:1599: UndefinedMetricWarning: F-score is ill-defined and being set to 0.0 in labels with no true nor predicted samples. Use `zero_division` parameter to control this behavior.\n",
      "  _warn_prf(average, \"true nor predicted\", \"F-score is\", len(true_sum))\n",
      "/home/pruthvish/JRF/RoadNetwork/RoadNetwork_VirtualEnv/lib/python3.8/site-packages/sklearn/metrics/_classification.py:1334: UndefinedMetricWarning: Precision is ill-defined and being set to 0.0 in labels with no predicted samples. Use `zero_division` parameter to control this behavior.\n",
      "  _warn_prf(average, modifier, msg_start, len(result))\n",
      "/home/pruthvish/JRF/RoadNetwork/RoadNetwork_VirtualEnv/lib/python3.8/site-packages/sklearn/metrics/_classification.py:1334: UndefinedMetricWarning: Recall is ill-defined and being set to 0.0 in labels with no true samples. Use `zero_division` parameter to control this behavior.\n",
      "  _warn_prf(average, modifier, msg_start, len(result))\n",
      "/home/pruthvish/JRF/RoadNetwork/RoadNetwork_VirtualEnv/lib/python3.8/site-packages/sklearn/metrics/_classification.py:1599: UndefinedMetricWarning: F-score is ill-defined and being set to 0.0 in labels with no true nor predicted samples. Use `zero_division` parameter to control this behavior.\n",
      "  _warn_prf(average, \"true nor predicted\", \"F-score is\", len(true_sum))\n",
      "/home/pruthvish/JRF/RoadNetwork/RoadNetwork_VirtualEnv/lib/python3.8/site-packages/sklearn/metrics/_classification.py:1334: UndefinedMetricWarning: Precision is ill-defined and being set to 0.0 in labels with no predicted samples. Use `zero_division` parameter to control this behavior.\n",
      "  _warn_prf(average, modifier, msg_start, len(result))\n",
      "/home/pruthvish/JRF/RoadNetwork/RoadNetwork_VirtualEnv/lib/python3.8/site-packages/sklearn/metrics/_classification.py:1334: UndefinedMetricWarning: Recall is ill-defined and being set to 0.0 in labels with no true samples. Use `zero_division` parameter to control this behavior.\n",
      "  _warn_prf(average, modifier, msg_start, len(result))\n",
      "/home/pruthvish/JRF/RoadNetwork/RoadNetwork_VirtualEnv/lib/python3.8/site-packages/sklearn/metrics/_classification.py:1599: UndefinedMetricWarning: F-score is ill-defined and being set to 0.0 in labels with no true nor predicted samples. Use `zero_division` parameter to control this behavior.\n",
      "  _warn_prf(average, \"true nor predicted\", \"F-score is\", len(true_sum))\n"
     ]
    },
    {
     "name": "stderr",
     "output_type": "stream",
     "text": [
      "/home/pruthvish/JRF/RoadNetwork/RoadNetwork_VirtualEnv/lib/python3.8/site-packages/sklearn/metrics/_classification.py:1334: UndefinedMetricWarning: Precision is ill-defined and being set to 0.0 in labels with no predicted samples. Use `zero_division` parameter to control this behavior.\n",
      "  _warn_prf(average, modifier, msg_start, len(result))\n",
      "/home/pruthvish/JRF/RoadNetwork/RoadNetwork_VirtualEnv/lib/python3.8/site-packages/sklearn/metrics/_classification.py:1334: UndefinedMetricWarning: Recall is ill-defined and being set to 0.0 in labels with no true samples. Use `zero_division` parameter to control this behavior.\n",
      "  _warn_prf(average, modifier, msg_start, len(result))\n",
      "/home/pruthvish/JRF/RoadNetwork/RoadNetwork_VirtualEnv/lib/python3.8/site-packages/sklearn/metrics/_classification.py:1599: UndefinedMetricWarning: F-score is ill-defined and being set to 0.0 in labels with no true nor predicted samples. Use `zero_division` parameter to control this behavior.\n",
      "  _warn_prf(average, \"true nor predicted\", \"F-score is\", len(true_sum))\n",
      "/home/pruthvish/JRF/RoadNetwork/RoadNetwork_VirtualEnv/lib/python3.8/site-packages/sklearn/metrics/_classification.py:1334: UndefinedMetricWarning: Precision is ill-defined and being set to 0.0 in labels with no predicted samples. Use `zero_division` parameter to control this behavior.\n",
      "  _warn_prf(average, modifier, msg_start, len(result))\n",
      "/home/pruthvish/JRF/RoadNetwork/RoadNetwork_VirtualEnv/lib/python3.8/site-packages/sklearn/metrics/_classification.py:1334: UndefinedMetricWarning: Recall is ill-defined and being set to 0.0 in labels with no true samples. Use `zero_division` parameter to control this behavior.\n",
      "  _warn_prf(average, modifier, msg_start, len(result))\n",
      "/home/pruthvish/JRF/RoadNetwork/RoadNetwork_VirtualEnv/lib/python3.8/site-packages/sklearn/metrics/_classification.py:1599: UndefinedMetricWarning: F-score is ill-defined and being set to 0.0 in labels with no true nor predicted samples. Use `zero_division` parameter to control this behavior.\n",
      "  _warn_prf(average, \"true nor predicted\", \"F-score is\", len(true_sum))\n",
      "/home/pruthvish/JRF/RoadNetwork/RoadNetwork_VirtualEnv/lib/python3.8/site-packages/sklearn/metrics/_classification.py:1334: UndefinedMetricWarning: Precision is ill-defined and being set to 0.0 in labels with no predicted samples. Use `zero_division` parameter to control this behavior.\n",
      "  _warn_prf(average, modifier, msg_start, len(result))\n",
      "/home/pruthvish/JRF/RoadNetwork/RoadNetwork_VirtualEnv/lib/python3.8/site-packages/sklearn/metrics/_classification.py:1334: UndefinedMetricWarning: Recall is ill-defined and being set to 0.0 in labels with no true samples. Use `zero_division` parameter to control this behavior.\n",
      "  _warn_prf(average, modifier, msg_start, len(result))\n",
      "/home/pruthvish/JRF/RoadNetwork/RoadNetwork_VirtualEnv/lib/python3.8/site-packages/sklearn/metrics/_classification.py:1599: UndefinedMetricWarning: F-score is ill-defined and being set to 0.0 in labels with no true nor predicted samples. Use `zero_division` parameter to control this behavior.\n",
      "  _warn_prf(average, \"true nor predicted\", \"F-score is\", len(true_sum))\n"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "Feature set-3\n"
     ]
    },
    {
     "name": "stderr",
     "output_type": "stream",
     "text": [
      "/home/pruthvish/JRF/RoadNetwork/RoadNetwork_VirtualEnv/lib/python3.8/site-packages/sklearn/metrics/_classification.py:1334: UndefinedMetricWarning: Precision is ill-defined and being set to 0.0 in labels with no predicted samples. Use `zero_division` parameter to control this behavior.\n",
      "  _warn_prf(average, modifier, msg_start, len(result))\n",
      "/home/pruthvish/JRF/RoadNetwork/RoadNetwork_VirtualEnv/lib/python3.8/site-packages/sklearn/metrics/_classification.py:1334: UndefinedMetricWarning: Recall is ill-defined and being set to 0.0 in labels with no true samples. Use `zero_division` parameter to control this behavior.\n",
      "  _warn_prf(average, modifier, msg_start, len(result))\n",
      "/home/pruthvish/JRF/RoadNetwork/RoadNetwork_VirtualEnv/lib/python3.8/site-packages/sklearn/metrics/_classification.py:1599: UndefinedMetricWarning: F-score is ill-defined and being set to 0.0 in labels with no true nor predicted samples. Use `zero_division` parameter to control this behavior.\n",
      "  _warn_prf(average, \"true nor predicted\", \"F-score is\", len(true_sum))\n",
      "/home/pruthvish/JRF/RoadNetwork/RoadNetwork_VirtualEnv/lib/python3.8/site-packages/sklearn/metrics/_classification.py:1334: UndefinedMetricWarning: Precision is ill-defined and being set to 0.0 in labels with no predicted samples. Use `zero_division` parameter to control this behavior.\n",
      "  _warn_prf(average, modifier, msg_start, len(result))\n",
      "/home/pruthvish/JRF/RoadNetwork/RoadNetwork_VirtualEnv/lib/python3.8/site-packages/sklearn/metrics/_classification.py:1334: UndefinedMetricWarning: Recall is ill-defined and being set to 0.0 in labels with no true samples. Use `zero_division` parameter to control this behavior.\n",
      "  _warn_prf(average, modifier, msg_start, len(result))\n",
      "/home/pruthvish/JRF/RoadNetwork/RoadNetwork_VirtualEnv/lib/python3.8/site-packages/sklearn/metrics/_classification.py:1599: UndefinedMetricWarning: F-score is ill-defined and being set to 0.0 in labels with no true nor predicted samples. Use `zero_division` parameter to control this behavior.\n",
      "  _warn_prf(average, \"true nor predicted\", \"F-score is\", len(true_sum))\n",
      "/home/pruthvish/JRF/RoadNetwork/RoadNetwork_VirtualEnv/lib/python3.8/site-packages/sklearn/metrics/_classification.py:1334: UndefinedMetricWarning: Precision is ill-defined and being set to 0.0 in labels with no predicted samples. Use `zero_division` parameter to control this behavior.\n",
      "  _warn_prf(average, modifier, msg_start, len(result))\n",
      "/home/pruthvish/JRF/RoadNetwork/RoadNetwork_VirtualEnv/lib/python3.8/site-packages/sklearn/metrics/_classification.py:1334: UndefinedMetricWarning: Recall is ill-defined and being set to 0.0 in labels with no true samples. Use `zero_division` parameter to control this behavior.\n",
      "  _warn_prf(average, modifier, msg_start, len(result))\n",
      "/home/pruthvish/JRF/RoadNetwork/RoadNetwork_VirtualEnv/lib/python3.8/site-packages/sklearn/metrics/_classification.py:1599: UndefinedMetricWarning: F-score is ill-defined and being set to 0.0 in labels with no true nor predicted samples. Use `zero_division` parameter to control this behavior.\n",
      "  _warn_prf(average, \"true nor predicted\", \"F-score is\", len(true_sum))\n",
      "/home/pruthvish/JRF/RoadNetwork/RoadNetwork_VirtualEnv/lib/python3.8/site-packages/sklearn/metrics/_classification.py:1334: UndefinedMetricWarning: Precision is ill-defined and being set to 0.0 in labels with no predicted samples. Use `zero_division` parameter to control this behavior.\n",
      "  _warn_prf(average, modifier, msg_start, len(result))\n",
      "/home/pruthvish/JRF/RoadNetwork/RoadNetwork_VirtualEnv/lib/python3.8/site-packages/sklearn/metrics/_classification.py:1334: UndefinedMetricWarning: Recall is ill-defined and being set to 0.0 in labels with no true samples. Use `zero_division` parameter to control this behavior.\n",
      "  _warn_prf(average, modifier, msg_start, len(result))\n",
      "/home/pruthvish/JRF/RoadNetwork/RoadNetwork_VirtualEnv/lib/python3.8/site-packages/sklearn/metrics/_classification.py:1599: UndefinedMetricWarning: F-score is ill-defined and being set to 0.0 in labels with no true nor predicted samples. Use `zero_division` parameter to control this behavior.\n",
      "  _warn_prf(average, \"true nor predicted\", \"F-score is\", len(true_sum))\n",
      "/home/pruthvish/JRF/RoadNetwork/RoadNetwork_VirtualEnv/lib/python3.8/site-packages/sklearn/metrics/_classification.py:1334: UndefinedMetricWarning: Precision is ill-defined and being set to 0.0 in labels with no predicted samples. Use `zero_division` parameter to control this behavior.\n",
      "  _warn_prf(average, modifier, msg_start, len(result))\n",
      "/home/pruthvish/JRF/RoadNetwork/RoadNetwork_VirtualEnv/lib/python3.8/site-packages/sklearn/metrics/_classification.py:1334: UndefinedMetricWarning: Recall is ill-defined and being set to 0.0 in labels with no true samples. Use `zero_division` parameter to control this behavior.\n",
      "  _warn_prf(average, modifier, msg_start, len(result))\n",
      "/home/pruthvish/JRF/RoadNetwork/RoadNetwork_VirtualEnv/lib/python3.8/site-packages/sklearn/metrics/_classification.py:1599: UndefinedMetricWarning: F-score is ill-defined and being set to 0.0 in labels with no true nor predicted samples. Use `zero_division` parameter to control this behavior.\n",
      "  _warn_prf(average, \"true nor predicted\", \"F-score is\", len(true_sum))\n",
      "/home/pruthvish/JRF/RoadNetwork/RoadNetwork_VirtualEnv/lib/python3.8/site-packages/sklearn/metrics/_classification.py:1334: UndefinedMetricWarning: Precision is ill-defined and being set to 0.0 in labels with no predicted samples. Use `zero_division` parameter to control this behavior.\n",
      "  _warn_prf(average, modifier, msg_start, len(result))\n",
      "/home/pruthvish/JRF/RoadNetwork/RoadNetwork_VirtualEnv/lib/python3.8/site-packages/sklearn/metrics/_classification.py:1334: UndefinedMetricWarning: Recall is ill-defined and being set to 0.0 in labels with no true samples. Use `zero_division` parameter to control this behavior.\n",
      "  _warn_prf(average, modifier, msg_start, len(result))\n",
      "/home/pruthvish/JRF/RoadNetwork/RoadNetwork_VirtualEnv/lib/python3.8/site-packages/sklearn/metrics/_classification.py:1599: UndefinedMetricWarning: F-score is ill-defined and being set to 0.0 in labels with no true nor predicted samples. Use `zero_division` parameter to control this behavior.\n",
      "  _warn_prf(average, \"true nor predicted\", \"F-score is\", len(true_sum))\n",
      "/home/pruthvish/JRF/RoadNetwork/RoadNetwork_VirtualEnv/lib/python3.8/site-packages/sklearn/metrics/_classification.py:1334: UndefinedMetricWarning: Precision is ill-defined and being set to 0.0 in labels with no predicted samples. Use `zero_division` parameter to control this behavior.\n",
      "  _warn_prf(average, modifier, msg_start, len(result))\n",
      "/home/pruthvish/JRF/RoadNetwork/RoadNetwork_VirtualEnv/lib/python3.8/site-packages/sklearn/metrics/_classification.py:1334: UndefinedMetricWarning: Recall is ill-defined and being set to 0.0 in labels with no true samples. Use `zero_division` parameter to control this behavior.\n",
      "  _warn_prf(average, modifier, msg_start, len(result))\n",
      "/home/pruthvish/JRF/RoadNetwork/RoadNetwork_VirtualEnv/lib/python3.8/site-packages/sklearn/metrics/_classification.py:1599: UndefinedMetricWarning: F-score is ill-defined and being set to 0.0 in labels with no true nor predicted samples. Use `zero_division` parameter to control this behavior.\n",
      "  _warn_prf(average, \"true nor predicted\", \"F-score is\", len(true_sum))\n",
      "/home/pruthvish/JRF/RoadNetwork/RoadNetwork_VirtualEnv/lib/python3.8/site-packages/sklearn/metrics/_classification.py:1334: UndefinedMetricWarning: Precision is ill-defined and being set to 0.0 in labels with no predicted samples. Use `zero_division` parameter to control this behavior.\n",
      "  _warn_prf(average, modifier, msg_start, len(result))\n",
      "/home/pruthvish/JRF/RoadNetwork/RoadNetwork_VirtualEnv/lib/python3.8/site-packages/sklearn/metrics/_classification.py:1334: UndefinedMetricWarning: Recall is ill-defined and being set to 0.0 in labels with no true samples. Use `zero_division` parameter to control this behavior.\n",
      "  _warn_prf(average, modifier, msg_start, len(result))\n",
      "/home/pruthvish/JRF/RoadNetwork/RoadNetwork_VirtualEnv/lib/python3.8/site-packages/sklearn/metrics/_classification.py:1599: UndefinedMetricWarning: F-score is ill-defined and being set to 0.0 in labels with no true nor predicted samples. Use `zero_division` parameter to control this behavior.\n",
      "  _warn_prf(average, \"true nor predicted\", \"F-score is\", len(true_sum))\n"
     ]
    },
    {
     "name": "stderr",
     "output_type": "stream",
     "text": [
      "/home/pruthvish/JRF/RoadNetwork/RoadNetwork_VirtualEnv/lib/python3.8/site-packages/sklearn/metrics/_classification.py:1334: UndefinedMetricWarning: Precision is ill-defined and being set to 0.0 in labels with no predicted samples. Use `zero_division` parameter to control this behavior.\n",
      "  _warn_prf(average, modifier, msg_start, len(result))\n",
      "/home/pruthvish/JRF/RoadNetwork/RoadNetwork_VirtualEnv/lib/python3.8/site-packages/sklearn/metrics/_classification.py:1334: UndefinedMetricWarning: Recall is ill-defined and being set to 0.0 in labels with no true samples. Use `zero_division` parameter to control this behavior.\n",
      "  _warn_prf(average, modifier, msg_start, len(result))\n",
      "/home/pruthvish/JRF/RoadNetwork/RoadNetwork_VirtualEnv/lib/python3.8/site-packages/sklearn/metrics/_classification.py:1599: UndefinedMetricWarning: F-score is ill-defined and being set to 0.0 in labels with no true nor predicted samples. Use `zero_division` parameter to control this behavior.\n",
      "  _warn_prf(average, \"true nor predicted\", \"F-score is\", len(true_sum))\n",
      "/home/pruthvish/JRF/RoadNetwork/RoadNetwork_VirtualEnv/lib/python3.8/site-packages/sklearn/metrics/_classification.py:1334: UndefinedMetricWarning: Precision is ill-defined and being set to 0.0 in labels with no predicted samples. Use `zero_division` parameter to control this behavior.\n",
      "  _warn_prf(average, modifier, msg_start, len(result))\n",
      "/home/pruthvish/JRF/RoadNetwork/RoadNetwork_VirtualEnv/lib/python3.8/site-packages/sklearn/metrics/_classification.py:1334: UndefinedMetricWarning: Recall is ill-defined and being set to 0.0 in labels with no true samples. Use `zero_division` parameter to control this behavior.\n",
      "  _warn_prf(average, modifier, msg_start, len(result))\n",
      "/home/pruthvish/JRF/RoadNetwork/RoadNetwork_VirtualEnv/lib/python3.8/site-packages/sklearn/metrics/_classification.py:1599: UndefinedMetricWarning: F-score is ill-defined and being set to 0.0 in labels with no true nor predicted samples. Use `zero_division` parameter to control this behavior.\n",
      "  _warn_prf(average, \"true nor predicted\", \"F-score is\", len(true_sum))\n",
      "/home/pruthvish/JRF/RoadNetwork/RoadNetwork_VirtualEnv/lib/python3.8/site-packages/sklearn/metrics/_classification.py:1334: UndefinedMetricWarning: Precision is ill-defined and being set to 0.0 in labels with no predicted samples. Use `zero_division` parameter to control this behavior.\n",
      "  _warn_prf(average, modifier, msg_start, len(result))\n",
      "/home/pruthvish/JRF/RoadNetwork/RoadNetwork_VirtualEnv/lib/python3.8/site-packages/sklearn/metrics/_classification.py:1334: UndefinedMetricWarning: Recall is ill-defined and being set to 0.0 in labels with no true samples. Use `zero_division` parameter to control this behavior.\n",
      "  _warn_prf(average, modifier, msg_start, len(result))\n",
      "/home/pruthvish/JRF/RoadNetwork/RoadNetwork_VirtualEnv/lib/python3.8/site-packages/sklearn/metrics/_classification.py:1599: UndefinedMetricWarning: F-score is ill-defined and being set to 0.0 in labels with no true nor predicted samples. Use `zero_division` parameter to control this behavior.\n",
      "  _warn_prf(average, \"true nor predicted\", \"F-score is\", len(true_sum))\n"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "Feature set-4\n"
     ]
    },
    {
     "name": "stderr",
     "output_type": "stream",
     "text": [
      "/home/pruthvish/JRF/RoadNetwork/RoadNetwork_VirtualEnv/lib/python3.8/site-packages/sklearn/metrics/_classification.py:1334: UndefinedMetricWarning: Precision is ill-defined and being set to 0.0 in labels with no predicted samples. Use `zero_division` parameter to control this behavior.\n",
      "  _warn_prf(average, modifier, msg_start, len(result))\n",
      "/home/pruthvish/JRF/RoadNetwork/RoadNetwork_VirtualEnv/lib/python3.8/site-packages/sklearn/metrics/_classification.py:1334: UndefinedMetricWarning: Recall is ill-defined and being set to 0.0 in labels with no true samples. Use `zero_division` parameter to control this behavior.\n",
      "  _warn_prf(average, modifier, msg_start, len(result))\n",
      "/home/pruthvish/JRF/RoadNetwork/RoadNetwork_VirtualEnv/lib/python3.8/site-packages/sklearn/metrics/_classification.py:1599: UndefinedMetricWarning: F-score is ill-defined and being set to 0.0 in labels with no true nor predicted samples. Use `zero_division` parameter to control this behavior.\n",
      "  _warn_prf(average, \"true nor predicted\", \"F-score is\", len(true_sum))\n",
      "/home/pruthvish/JRF/RoadNetwork/RoadNetwork_VirtualEnv/lib/python3.8/site-packages/sklearn/metrics/_classification.py:1334: UndefinedMetricWarning: Precision is ill-defined and being set to 0.0 in labels with no predicted samples. Use `zero_division` parameter to control this behavior.\n",
      "  _warn_prf(average, modifier, msg_start, len(result))\n",
      "/home/pruthvish/JRF/RoadNetwork/RoadNetwork_VirtualEnv/lib/python3.8/site-packages/sklearn/metrics/_classification.py:1334: UndefinedMetricWarning: Recall is ill-defined and being set to 0.0 in labels with no true samples. Use `zero_division` parameter to control this behavior.\n",
      "  _warn_prf(average, modifier, msg_start, len(result))\n",
      "/home/pruthvish/JRF/RoadNetwork/RoadNetwork_VirtualEnv/lib/python3.8/site-packages/sklearn/metrics/_classification.py:1599: UndefinedMetricWarning: F-score is ill-defined and being set to 0.0 in labels with no true nor predicted samples. Use `zero_division` parameter to control this behavior.\n",
      "  _warn_prf(average, \"true nor predicted\", \"F-score is\", len(true_sum))\n",
      "/home/pruthvish/JRF/RoadNetwork/RoadNetwork_VirtualEnv/lib/python3.8/site-packages/sklearn/metrics/_classification.py:1334: UndefinedMetricWarning: Precision is ill-defined and being set to 0.0 in labels with no predicted samples. Use `zero_division` parameter to control this behavior.\n",
      "  _warn_prf(average, modifier, msg_start, len(result))\n",
      "/home/pruthvish/JRF/RoadNetwork/RoadNetwork_VirtualEnv/lib/python3.8/site-packages/sklearn/metrics/_classification.py:1334: UndefinedMetricWarning: Recall is ill-defined and being set to 0.0 in labels with no true samples. Use `zero_division` parameter to control this behavior.\n",
      "  _warn_prf(average, modifier, msg_start, len(result))\n",
      "/home/pruthvish/JRF/RoadNetwork/RoadNetwork_VirtualEnv/lib/python3.8/site-packages/sklearn/metrics/_classification.py:1599: UndefinedMetricWarning: F-score is ill-defined and being set to 0.0 in labels with no true nor predicted samples. Use `zero_division` parameter to control this behavior.\n",
      "  _warn_prf(average, \"true nor predicted\", \"F-score is\", len(true_sum))\n",
      "/home/pruthvish/JRF/RoadNetwork/RoadNetwork_VirtualEnv/lib/python3.8/site-packages/sklearn/metrics/_classification.py:1334: UndefinedMetricWarning: Precision is ill-defined and being set to 0.0 in labels with no predicted samples. Use `zero_division` parameter to control this behavior.\n",
      "  _warn_prf(average, modifier, msg_start, len(result))\n",
      "/home/pruthvish/JRF/RoadNetwork/RoadNetwork_VirtualEnv/lib/python3.8/site-packages/sklearn/metrics/_classification.py:1334: UndefinedMetricWarning: Recall is ill-defined and being set to 0.0 in labels with no true samples. Use `zero_division` parameter to control this behavior.\n",
      "  _warn_prf(average, modifier, msg_start, len(result))\n",
      "/home/pruthvish/JRF/RoadNetwork/RoadNetwork_VirtualEnv/lib/python3.8/site-packages/sklearn/metrics/_classification.py:1599: UndefinedMetricWarning: F-score is ill-defined and being set to 0.0 in labels with no true nor predicted samples. Use `zero_division` parameter to control this behavior.\n",
      "  _warn_prf(average, \"true nor predicted\", \"F-score is\", len(true_sum))\n",
      "/home/pruthvish/JRF/RoadNetwork/RoadNetwork_VirtualEnv/lib/python3.8/site-packages/sklearn/metrics/_classification.py:1334: UndefinedMetricWarning: Precision is ill-defined and being set to 0.0 in labels with no predicted samples. Use `zero_division` parameter to control this behavior.\n",
      "  _warn_prf(average, modifier, msg_start, len(result))\n",
      "/home/pruthvish/JRF/RoadNetwork/RoadNetwork_VirtualEnv/lib/python3.8/site-packages/sklearn/metrics/_classification.py:1334: UndefinedMetricWarning: Recall is ill-defined and being set to 0.0 in labels with no true samples. Use `zero_division` parameter to control this behavior.\n",
      "  _warn_prf(average, modifier, msg_start, len(result))\n",
      "/home/pruthvish/JRF/RoadNetwork/RoadNetwork_VirtualEnv/lib/python3.8/site-packages/sklearn/metrics/_classification.py:1599: UndefinedMetricWarning: F-score is ill-defined and being set to 0.0 in labels with no true nor predicted samples. Use `zero_division` parameter to control this behavior.\n",
      "  _warn_prf(average, \"true nor predicted\", \"F-score is\", len(true_sum))\n",
      "/home/pruthvish/JRF/RoadNetwork/RoadNetwork_VirtualEnv/lib/python3.8/site-packages/sklearn/metrics/_classification.py:1334: UndefinedMetricWarning: Precision is ill-defined and being set to 0.0 in labels with no predicted samples. Use `zero_division` parameter to control this behavior.\n",
      "  _warn_prf(average, modifier, msg_start, len(result))\n",
      "/home/pruthvish/JRF/RoadNetwork/RoadNetwork_VirtualEnv/lib/python3.8/site-packages/sklearn/metrics/_classification.py:1334: UndefinedMetricWarning: Recall is ill-defined and being set to 0.0 in labels with no true samples. Use `zero_division` parameter to control this behavior.\n",
      "  _warn_prf(average, modifier, msg_start, len(result))\n",
      "/home/pruthvish/JRF/RoadNetwork/RoadNetwork_VirtualEnv/lib/python3.8/site-packages/sklearn/metrics/_classification.py:1599: UndefinedMetricWarning: F-score is ill-defined and being set to 0.0 in labels with no true nor predicted samples. Use `zero_division` parameter to control this behavior.\n",
      "  _warn_prf(average, \"true nor predicted\", \"F-score is\", len(true_sum))\n",
      "/home/pruthvish/JRF/RoadNetwork/RoadNetwork_VirtualEnv/lib/python3.8/site-packages/sklearn/metrics/_classification.py:1334: UndefinedMetricWarning: Precision is ill-defined and being set to 0.0 in labels with no predicted samples. Use `zero_division` parameter to control this behavior.\n",
      "  _warn_prf(average, modifier, msg_start, len(result))\n",
      "/home/pruthvish/JRF/RoadNetwork/RoadNetwork_VirtualEnv/lib/python3.8/site-packages/sklearn/metrics/_classification.py:1334: UndefinedMetricWarning: Recall is ill-defined and being set to 0.0 in labels with no true samples. Use `zero_division` parameter to control this behavior.\n",
      "  _warn_prf(average, modifier, msg_start, len(result))\n",
      "/home/pruthvish/JRF/RoadNetwork/RoadNetwork_VirtualEnv/lib/python3.8/site-packages/sklearn/metrics/_classification.py:1599: UndefinedMetricWarning: F-score is ill-defined and being set to 0.0 in labels with no true nor predicted samples. Use `zero_division` parameter to control this behavior.\n",
      "  _warn_prf(average, \"true nor predicted\", \"F-score is\", len(true_sum))\n",
      "/home/pruthvish/JRF/RoadNetwork/RoadNetwork_VirtualEnv/lib/python3.8/site-packages/sklearn/metrics/_classification.py:1334: UndefinedMetricWarning: Precision is ill-defined and being set to 0.0 in labels with no predicted samples. Use `zero_division` parameter to control this behavior.\n",
      "  _warn_prf(average, modifier, msg_start, len(result))\n",
      "/home/pruthvish/JRF/RoadNetwork/RoadNetwork_VirtualEnv/lib/python3.8/site-packages/sklearn/metrics/_classification.py:1334: UndefinedMetricWarning: Recall is ill-defined and being set to 0.0 in labels with no true samples. Use `zero_division` parameter to control this behavior.\n",
      "  _warn_prf(average, modifier, msg_start, len(result))\n",
      "/home/pruthvish/JRF/RoadNetwork/RoadNetwork_VirtualEnv/lib/python3.8/site-packages/sklearn/metrics/_classification.py:1599: UndefinedMetricWarning: F-score is ill-defined and being set to 0.0 in labels with no true nor predicted samples. Use `zero_division` parameter to control this behavior.\n",
      "  _warn_prf(average, \"true nor predicted\", \"F-score is\", len(true_sum))\n"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "Classifier, ClassifierName SVC(gamma='auto') SVC\n",
      "Feature set-1\n"
     ]
    },
    {
     "name": "stderr",
     "output_type": "stream",
     "text": [
      "/home/pruthvish/JRF/RoadNetwork/RoadNetwork_VirtualEnv/lib/python3.8/site-packages/sklearn/metrics/_classification.py:1334: UndefinedMetricWarning: Precision is ill-defined and being set to 0.0 in labels with no predicted samples. Use `zero_division` parameter to control this behavior.\n",
      "  _warn_prf(average, modifier, msg_start, len(result))\n",
      "/home/pruthvish/JRF/RoadNetwork/RoadNetwork_VirtualEnv/lib/python3.8/site-packages/sklearn/metrics/_classification.py:1334: UndefinedMetricWarning: Recall is ill-defined and being set to 0.0 in labels with no true samples. Use `zero_division` parameter to control this behavior.\n",
      "  _warn_prf(average, modifier, msg_start, len(result))\n",
      "/home/pruthvish/JRF/RoadNetwork/RoadNetwork_VirtualEnv/lib/python3.8/site-packages/sklearn/metrics/_classification.py:1599: UndefinedMetricWarning: F-score is ill-defined and being set to 0.0 in labels with no true nor predicted samples. Use `zero_division` parameter to control this behavior.\n",
      "  _warn_prf(average, \"true nor predicted\", \"F-score is\", len(true_sum))\n",
      "/home/pruthvish/JRF/RoadNetwork/RoadNetwork_VirtualEnv/lib/python3.8/site-packages/sklearn/metrics/_classification.py:1334: UndefinedMetricWarning: Precision is ill-defined and being set to 0.0 in labels with no predicted samples. Use `zero_division` parameter to control this behavior.\n",
      "  _warn_prf(average, modifier, msg_start, len(result))\n",
      "/home/pruthvish/JRF/RoadNetwork/RoadNetwork_VirtualEnv/lib/python3.8/site-packages/sklearn/metrics/_classification.py:1334: UndefinedMetricWarning: Recall is ill-defined and being set to 0.0 in labels with no true samples. Use `zero_division` parameter to control this behavior.\n",
      "  _warn_prf(average, modifier, msg_start, len(result))\n",
      "/home/pruthvish/JRF/RoadNetwork/RoadNetwork_VirtualEnv/lib/python3.8/site-packages/sklearn/metrics/_classification.py:1599: UndefinedMetricWarning: F-score is ill-defined and being set to 0.0 in labels with no true nor predicted samples. Use `zero_division` parameter to control this behavior.\n",
      "  _warn_prf(average, \"true nor predicted\", \"F-score is\", len(true_sum))\n",
      "/home/pruthvish/JRF/RoadNetwork/RoadNetwork_VirtualEnv/lib/python3.8/site-packages/sklearn/metrics/_classification.py:1334: UndefinedMetricWarning: Precision is ill-defined and being set to 0.0 in labels with no predicted samples. Use `zero_division` parameter to control this behavior.\n",
      "  _warn_prf(average, modifier, msg_start, len(result))\n",
      "/home/pruthvish/JRF/RoadNetwork/RoadNetwork_VirtualEnv/lib/python3.8/site-packages/sklearn/metrics/_classification.py:1334: UndefinedMetricWarning: Recall is ill-defined and being set to 0.0 in labels with no true samples. Use `zero_division` parameter to control this behavior.\n",
      "  _warn_prf(average, modifier, msg_start, len(result))\n",
      "/home/pruthvish/JRF/RoadNetwork/RoadNetwork_VirtualEnv/lib/python3.8/site-packages/sklearn/metrics/_classification.py:1599: UndefinedMetricWarning: F-score is ill-defined and being set to 0.0 in labels with no true nor predicted samples. Use `zero_division` parameter to control this behavior.\n",
      "  _warn_prf(average, \"true nor predicted\", \"F-score is\", len(true_sum))\n",
      "/home/pruthvish/JRF/RoadNetwork/RoadNetwork_VirtualEnv/lib/python3.8/site-packages/sklearn/metrics/_classification.py:1334: UndefinedMetricWarning: Precision is ill-defined and being set to 0.0 in labels with no predicted samples. Use `zero_division` parameter to control this behavior.\n",
      "  _warn_prf(average, modifier, msg_start, len(result))\n",
      "/home/pruthvish/JRF/RoadNetwork/RoadNetwork_VirtualEnv/lib/python3.8/site-packages/sklearn/metrics/_classification.py:1334: UndefinedMetricWarning: Recall is ill-defined and being set to 0.0 in labels with no true samples. Use `zero_division` parameter to control this behavior.\n",
      "  _warn_prf(average, modifier, msg_start, len(result))\n",
      "/home/pruthvish/JRF/RoadNetwork/RoadNetwork_VirtualEnv/lib/python3.8/site-packages/sklearn/metrics/_classification.py:1599: UndefinedMetricWarning: F-score is ill-defined and being set to 0.0 in labels with no true nor predicted samples. Use `zero_division` parameter to control this behavior.\n",
      "  _warn_prf(average, \"true nor predicted\", \"F-score is\", len(true_sum))\n",
      "/home/pruthvish/JRF/RoadNetwork/RoadNetwork_VirtualEnv/lib/python3.8/site-packages/sklearn/metrics/_classification.py:1334: UndefinedMetricWarning: Precision is ill-defined and being set to 0.0 in labels with no predicted samples. Use `zero_division` parameter to control this behavior.\n",
      "  _warn_prf(average, modifier, msg_start, len(result))\n",
      "/home/pruthvish/JRF/RoadNetwork/RoadNetwork_VirtualEnv/lib/python3.8/site-packages/sklearn/metrics/_classification.py:1334: UndefinedMetricWarning: Recall is ill-defined and being set to 0.0 in labels with no true samples. Use `zero_division` parameter to control this behavior.\n",
      "  _warn_prf(average, modifier, msg_start, len(result))\n",
      "/home/pruthvish/JRF/RoadNetwork/RoadNetwork_VirtualEnv/lib/python3.8/site-packages/sklearn/metrics/_classification.py:1599: UndefinedMetricWarning: F-score is ill-defined and being set to 0.0 in labels with no true nor predicted samples. Use `zero_division` parameter to control this behavior.\n",
      "  _warn_prf(average, \"true nor predicted\", \"F-score is\", len(true_sum))\n",
      "/home/pruthvish/JRF/RoadNetwork/RoadNetwork_VirtualEnv/lib/python3.8/site-packages/sklearn/metrics/_classification.py:1334: UndefinedMetricWarning: Precision is ill-defined and being set to 0.0 in labels with no predicted samples. Use `zero_division` parameter to control this behavior.\n",
      "  _warn_prf(average, modifier, msg_start, len(result))\n",
      "/home/pruthvish/JRF/RoadNetwork/RoadNetwork_VirtualEnv/lib/python3.8/site-packages/sklearn/metrics/_classification.py:1334: UndefinedMetricWarning: Recall is ill-defined and being set to 0.0 in labels with no true samples. Use `zero_division` parameter to control this behavior.\n",
      "  _warn_prf(average, modifier, msg_start, len(result))\n",
      "/home/pruthvish/JRF/RoadNetwork/RoadNetwork_VirtualEnv/lib/python3.8/site-packages/sklearn/metrics/_classification.py:1599: UndefinedMetricWarning: F-score is ill-defined and being set to 0.0 in labels with no true nor predicted samples. Use `zero_division` parameter to control this behavior.\n",
      "  _warn_prf(average, \"true nor predicted\", \"F-score is\", len(true_sum))\n",
      "/home/pruthvish/JRF/RoadNetwork/RoadNetwork_VirtualEnv/lib/python3.8/site-packages/sklearn/metrics/_classification.py:1334: UndefinedMetricWarning: Precision is ill-defined and being set to 0.0 in labels with no predicted samples. Use `zero_division` parameter to control this behavior.\n",
      "  _warn_prf(average, modifier, msg_start, len(result))\n",
      "/home/pruthvish/JRF/RoadNetwork/RoadNetwork_VirtualEnv/lib/python3.8/site-packages/sklearn/metrics/_classification.py:1334: UndefinedMetricWarning: Recall is ill-defined and being set to 0.0 in labels with no true samples. Use `zero_division` parameter to control this behavior.\n",
      "  _warn_prf(average, modifier, msg_start, len(result))\n",
      "/home/pruthvish/JRF/RoadNetwork/RoadNetwork_VirtualEnv/lib/python3.8/site-packages/sklearn/metrics/_classification.py:1599: UndefinedMetricWarning: F-score is ill-defined and being set to 0.0 in labels with no true nor predicted samples. Use `zero_division` parameter to control this behavior.\n",
      "  _warn_prf(average, \"true nor predicted\", \"F-score is\", len(true_sum))\n",
      "/home/pruthvish/JRF/RoadNetwork/RoadNetwork_VirtualEnv/lib/python3.8/site-packages/sklearn/metrics/_classification.py:1334: UndefinedMetricWarning: Precision is ill-defined and being set to 0.0 in labels with no predicted samples. Use `zero_division` parameter to control this behavior.\n",
      "  _warn_prf(average, modifier, msg_start, len(result))\n",
      "/home/pruthvish/JRF/RoadNetwork/RoadNetwork_VirtualEnv/lib/python3.8/site-packages/sklearn/metrics/_classification.py:1334: UndefinedMetricWarning: Recall is ill-defined and being set to 0.0 in labels with no true samples. Use `zero_division` parameter to control this behavior.\n",
      "  _warn_prf(average, modifier, msg_start, len(result))\n",
      "/home/pruthvish/JRF/RoadNetwork/RoadNetwork_VirtualEnv/lib/python3.8/site-packages/sklearn/metrics/_classification.py:1599: UndefinedMetricWarning: F-score is ill-defined and being set to 0.0 in labels with no true nor predicted samples. Use `zero_division` parameter to control this behavior.\n",
      "  _warn_prf(average, \"true nor predicted\", \"F-score is\", len(true_sum))\n"
     ]
    },
    {
     "name": "stderr",
     "output_type": "stream",
     "text": [
      "/home/pruthvish/JRF/RoadNetwork/RoadNetwork_VirtualEnv/lib/python3.8/site-packages/sklearn/metrics/_classification.py:1334: UndefinedMetricWarning: Precision is ill-defined and being set to 0.0 in labels with no predicted samples. Use `zero_division` parameter to control this behavior.\n",
      "  _warn_prf(average, modifier, msg_start, len(result))\n",
      "/home/pruthvish/JRF/RoadNetwork/RoadNetwork_VirtualEnv/lib/python3.8/site-packages/sklearn/metrics/_classification.py:1334: UndefinedMetricWarning: Recall is ill-defined and being set to 0.0 in labels with no true samples. Use `zero_division` parameter to control this behavior.\n",
      "  _warn_prf(average, modifier, msg_start, len(result))\n",
      "/home/pruthvish/JRF/RoadNetwork/RoadNetwork_VirtualEnv/lib/python3.8/site-packages/sklearn/metrics/_classification.py:1599: UndefinedMetricWarning: F-score is ill-defined and being set to 0.0 in labels with no true nor predicted samples. Use `zero_division` parameter to control this behavior.\n",
      "  _warn_prf(average, \"true nor predicted\", \"F-score is\", len(true_sum))\n",
      "/home/pruthvish/JRF/RoadNetwork/RoadNetwork_VirtualEnv/lib/python3.8/site-packages/sklearn/metrics/_classification.py:1334: UndefinedMetricWarning: Precision is ill-defined and being set to 0.0 in labels with no predicted samples. Use `zero_division` parameter to control this behavior.\n",
      "  _warn_prf(average, modifier, msg_start, len(result))\n",
      "/home/pruthvish/JRF/RoadNetwork/RoadNetwork_VirtualEnv/lib/python3.8/site-packages/sklearn/metrics/_classification.py:1334: UndefinedMetricWarning: Recall is ill-defined and being set to 0.0 in labels with no true samples. Use `zero_division` parameter to control this behavior.\n",
      "  _warn_prf(average, modifier, msg_start, len(result))\n",
      "/home/pruthvish/JRF/RoadNetwork/RoadNetwork_VirtualEnv/lib/python3.8/site-packages/sklearn/metrics/_classification.py:1599: UndefinedMetricWarning: F-score is ill-defined and being set to 0.0 in labels with no true nor predicted samples. Use `zero_division` parameter to control this behavior.\n",
      "  _warn_prf(average, \"true nor predicted\", \"F-score is\", len(true_sum))\n"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "Feature set-2\n"
     ]
    },
    {
     "name": "stderr",
     "output_type": "stream",
     "text": [
      "/home/pruthvish/JRF/RoadNetwork/RoadNetwork_VirtualEnv/lib/python3.8/site-packages/sklearn/metrics/_classification.py:1334: UndefinedMetricWarning: Precision is ill-defined and being set to 0.0 in labels with no predicted samples. Use `zero_division` parameter to control this behavior.\n",
      "  _warn_prf(average, modifier, msg_start, len(result))\n",
      "/home/pruthvish/JRF/RoadNetwork/RoadNetwork_VirtualEnv/lib/python3.8/site-packages/sklearn/metrics/_classification.py:1334: UndefinedMetricWarning: Recall is ill-defined and being set to 0.0 in labels with no true samples. Use `zero_division` parameter to control this behavior.\n",
      "  _warn_prf(average, modifier, msg_start, len(result))\n",
      "/home/pruthvish/JRF/RoadNetwork/RoadNetwork_VirtualEnv/lib/python3.8/site-packages/sklearn/metrics/_classification.py:1599: UndefinedMetricWarning: F-score is ill-defined and being set to 0.0 in labels with no true nor predicted samples. Use `zero_division` parameter to control this behavior.\n",
      "  _warn_prf(average, \"true nor predicted\", \"F-score is\", len(true_sum))\n",
      "/home/pruthvish/JRF/RoadNetwork/RoadNetwork_VirtualEnv/lib/python3.8/site-packages/sklearn/metrics/_classification.py:1334: UndefinedMetricWarning: Precision is ill-defined and being set to 0.0 in labels with no predicted samples. Use `zero_division` parameter to control this behavior.\n",
      "  _warn_prf(average, modifier, msg_start, len(result))\n",
      "/home/pruthvish/JRF/RoadNetwork/RoadNetwork_VirtualEnv/lib/python3.8/site-packages/sklearn/metrics/_classification.py:1334: UndefinedMetricWarning: Recall is ill-defined and being set to 0.0 in labels with no true samples. Use `zero_division` parameter to control this behavior.\n",
      "  _warn_prf(average, modifier, msg_start, len(result))\n",
      "/home/pruthvish/JRF/RoadNetwork/RoadNetwork_VirtualEnv/lib/python3.8/site-packages/sklearn/metrics/_classification.py:1599: UndefinedMetricWarning: F-score is ill-defined and being set to 0.0 in labels with no true nor predicted samples. Use `zero_division` parameter to control this behavior.\n",
      "  _warn_prf(average, \"true nor predicted\", \"F-score is\", len(true_sum))\n",
      "/home/pruthvish/JRF/RoadNetwork/RoadNetwork_VirtualEnv/lib/python3.8/site-packages/sklearn/metrics/_classification.py:1334: UndefinedMetricWarning: Precision is ill-defined and being set to 0.0 in labels with no predicted samples. Use `zero_division` parameter to control this behavior.\n",
      "  _warn_prf(average, modifier, msg_start, len(result))\n",
      "/home/pruthvish/JRF/RoadNetwork/RoadNetwork_VirtualEnv/lib/python3.8/site-packages/sklearn/metrics/_classification.py:1334: UndefinedMetricWarning: Recall is ill-defined and being set to 0.0 in labels with no true samples. Use `zero_division` parameter to control this behavior.\n",
      "  _warn_prf(average, modifier, msg_start, len(result))\n",
      "/home/pruthvish/JRF/RoadNetwork/RoadNetwork_VirtualEnv/lib/python3.8/site-packages/sklearn/metrics/_classification.py:1599: UndefinedMetricWarning: F-score is ill-defined and being set to 0.0 in labels with no true nor predicted samples. Use `zero_division` parameter to control this behavior.\n",
      "  _warn_prf(average, \"true nor predicted\", \"F-score is\", len(true_sum))\n",
      "/home/pruthvish/JRF/RoadNetwork/RoadNetwork_VirtualEnv/lib/python3.8/site-packages/sklearn/metrics/_classification.py:1334: UndefinedMetricWarning: Precision is ill-defined and being set to 0.0 in labels with no predicted samples. Use `zero_division` parameter to control this behavior.\n",
      "  _warn_prf(average, modifier, msg_start, len(result))\n",
      "/home/pruthvish/JRF/RoadNetwork/RoadNetwork_VirtualEnv/lib/python3.8/site-packages/sklearn/metrics/_classification.py:1334: UndefinedMetricWarning: Recall is ill-defined and being set to 0.0 in labels with no true samples. Use `zero_division` parameter to control this behavior.\n",
      "  _warn_prf(average, modifier, msg_start, len(result))\n",
      "/home/pruthvish/JRF/RoadNetwork/RoadNetwork_VirtualEnv/lib/python3.8/site-packages/sklearn/metrics/_classification.py:1599: UndefinedMetricWarning: F-score is ill-defined and being set to 0.0 in labels with no true nor predicted samples. Use `zero_division` parameter to control this behavior.\n",
      "  _warn_prf(average, \"true nor predicted\", \"F-score is\", len(true_sum))\n",
      "/home/pruthvish/JRF/RoadNetwork/RoadNetwork_VirtualEnv/lib/python3.8/site-packages/sklearn/metrics/_classification.py:1334: UndefinedMetricWarning: Precision is ill-defined and being set to 0.0 in labels with no predicted samples. Use `zero_division` parameter to control this behavior.\n",
      "  _warn_prf(average, modifier, msg_start, len(result))\n",
      "/home/pruthvish/JRF/RoadNetwork/RoadNetwork_VirtualEnv/lib/python3.8/site-packages/sklearn/metrics/_classification.py:1334: UndefinedMetricWarning: Recall is ill-defined and being set to 0.0 in labels with no true samples. Use `zero_division` parameter to control this behavior.\n",
      "  _warn_prf(average, modifier, msg_start, len(result))\n",
      "/home/pruthvish/JRF/RoadNetwork/RoadNetwork_VirtualEnv/lib/python3.8/site-packages/sklearn/metrics/_classification.py:1599: UndefinedMetricWarning: F-score is ill-defined and being set to 0.0 in labels with no true nor predicted samples. Use `zero_division` parameter to control this behavior.\n",
      "  _warn_prf(average, \"true nor predicted\", \"F-score is\", len(true_sum))\n",
      "/home/pruthvish/JRF/RoadNetwork/RoadNetwork_VirtualEnv/lib/python3.8/site-packages/sklearn/metrics/_classification.py:1334: UndefinedMetricWarning: Precision is ill-defined and being set to 0.0 in labels with no predicted samples. Use `zero_division` parameter to control this behavior.\n",
      "  _warn_prf(average, modifier, msg_start, len(result))\n",
      "/home/pruthvish/JRF/RoadNetwork/RoadNetwork_VirtualEnv/lib/python3.8/site-packages/sklearn/metrics/_classification.py:1334: UndefinedMetricWarning: Recall is ill-defined and being set to 0.0 in labels with no true samples. Use `zero_division` parameter to control this behavior.\n",
      "  _warn_prf(average, modifier, msg_start, len(result))\n",
      "/home/pruthvish/JRF/RoadNetwork/RoadNetwork_VirtualEnv/lib/python3.8/site-packages/sklearn/metrics/_classification.py:1599: UndefinedMetricWarning: F-score is ill-defined and being set to 0.0 in labels with no true nor predicted samples. Use `zero_division` parameter to control this behavior.\n",
      "  _warn_prf(average, \"true nor predicted\", \"F-score is\", len(true_sum))\n",
      "/home/pruthvish/JRF/RoadNetwork/RoadNetwork_VirtualEnv/lib/python3.8/site-packages/sklearn/metrics/_classification.py:1334: UndefinedMetricWarning: Precision is ill-defined and being set to 0.0 in labels with no predicted samples. Use `zero_division` parameter to control this behavior.\n",
      "  _warn_prf(average, modifier, msg_start, len(result))\n",
      "/home/pruthvish/JRF/RoadNetwork/RoadNetwork_VirtualEnv/lib/python3.8/site-packages/sklearn/metrics/_classification.py:1334: UndefinedMetricWarning: Recall is ill-defined and being set to 0.0 in labels with no true samples. Use `zero_division` parameter to control this behavior.\n",
      "  _warn_prf(average, modifier, msg_start, len(result))\n",
      "/home/pruthvish/JRF/RoadNetwork/RoadNetwork_VirtualEnv/lib/python3.8/site-packages/sklearn/metrics/_classification.py:1599: UndefinedMetricWarning: F-score is ill-defined and being set to 0.0 in labels with no true nor predicted samples. Use `zero_division` parameter to control this behavior.\n",
      "  _warn_prf(average, \"true nor predicted\", \"F-score is\", len(true_sum))\n",
      "/home/pruthvish/JRF/RoadNetwork/RoadNetwork_VirtualEnv/lib/python3.8/site-packages/sklearn/metrics/_classification.py:1334: UndefinedMetricWarning: Precision is ill-defined and being set to 0.0 in labels with no predicted samples. Use `zero_division` parameter to control this behavior.\n",
      "  _warn_prf(average, modifier, msg_start, len(result))\n",
      "/home/pruthvish/JRF/RoadNetwork/RoadNetwork_VirtualEnv/lib/python3.8/site-packages/sklearn/metrics/_classification.py:1334: UndefinedMetricWarning: Recall is ill-defined and being set to 0.0 in labels with no true samples. Use `zero_division` parameter to control this behavior.\n",
      "  _warn_prf(average, modifier, msg_start, len(result))\n",
      "/home/pruthvish/JRF/RoadNetwork/RoadNetwork_VirtualEnv/lib/python3.8/site-packages/sklearn/metrics/_classification.py:1599: UndefinedMetricWarning: F-score is ill-defined and being set to 0.0 in labels with no true nor predicted samples. Use `zero_division` parameter to control this behavior.\n",
      "  _warn_prf(average, \"true nor predicted\", \"F-score is\", len(true_sum))\n"
     ]
    },
    {
     "name": "stderr",
     "output_type": "stream",
     "text": [
      "/home/pruthvish/JRF/RoadNetwork/RoadNetwork_VirtualEnv/lib/python3.8/site-packages/sklearn/metrics/_classification.py:1334: UndefinedMetricWarning: Precision is ill-defined and being set to 0.0 in labels with no predicted samples. Use `zero_division` parameter to control this behavior.\n",
      "  _warn_prf(average, modifier, msg_start, len(result))\n",
      "/home/pruthvish/JRF/RoadNetwork/RoadNetwork_VirtualEnv/lib/python3.8/site-packages/sklearn/metrics/_classification.py:1334: UndefinedMetricWarning: Recall is ill-defined and being set to 0.0 in labels with no true samples. Use `zero_division` parameter to control this behavior.\n",
      "  _warn_prf(average, modifier, msg_start, len(result))\n",
      "/home/pruthvish/JRF/RoadNetwork/RoadNetwork_VirtualEnv/lib/python3.8/site-packages/sklearn/metrics/_classification.py:1599: UndefinedMetricWarning: F-score is ill-defined and being set to 0.0 in labels with no true nor predicted samples. Use `zero_division` parameter to control this behavior.\n",
      "  _warn_prf(average, \"true nor predicted\", \"F-score is\", len(true_sum))\n",
      "/home/pruthvish/JRF/RoadNetwork/RoadNetwork_VirtualEnv/lib/python3.8/site-packages/sklearn/metrics/_classification.py:1334: UndefinedMetricWarning: Precision is ill-defined and being set to 0.0 in labels with no predicted samples. Use `zero_division` parameter to control this behavior.\n",
      "  _warn_prf(average, modifier, msg_start, len(result))\n",
      "/home/pruthvish/JRF/RoadNetwork/RoadNetwork_VirtualEnv/lib/python3.8/site-packages/sklearn/metrics/_classification.py:1334: UndefinedMetricWarning: Recall is ill-defined and being set to 0.0 in labels with no true samples. Use `zero_division` parameter to control this behavior.\n",
      "  _warn_prf(average, modifier, msg_start, len(result))\n",
      "/home/pruthvish/JRF/RoadNetwork/RoadNetwork_VirtualEnv/lib/python3.8/site-packages/sklearn/metrics/_classification.py:1599: UndefinedMetricWarning: F-score is ill-defined and being set to 0.0 in labels with no true nor predicted samples. Use `zero_division` parameter to control this behavior.\n",
      "  _warn_prf(average, \"true nor predicted\", \"F-score is\", len(true_sum))\n"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "Feature set-3\n"
     ]
    },
    {
     "name": "stderr",
     "output_type": "stream",
     "text": [
      "/home/pruthvish/JRF/RoadNetwork/RoadNetwork_VirtualEnv/lib/python3.8/site-packages/sklearn/metrics/_classification.py:1334: UndefinedMetricWarning: Precision is ill-defined and being set to 0.0 in labels with no predicted samples. Use `zero_division` parameter to control this behavior.\n",
      "  _warn_prf(average, modifier, msg_start, len(result))\n",
      "/home/pruthvish/JRF/RoadNetwork/RoadNetwork_VirtualEnv/lib/python3.8/site-packages/sklearn/metrics/_classification.py:1334: UndefinedMetricWarning: Recall is ill-defined and being set to 0.0 in labels with no true samples. Use `zero_division` parameter to control this behavior.\n",
      "  _warn_prf(average, modifier, msg_start, len(result))\n",
      "/home/pruthvish/JRF/RoadNetwork/RoadNetwork_VirtualEnv/lib/python3.8/site-packages/sklearn/metrics/_classification.py:1599: UndefinedMetricWarning: F-score is ill-defined and being set to 0.0 in labels with no true nor predicted samples. Use `zero_division` parameter to control this behavior.\n",
      "  _warn_prf(average, \"true nor predicted\", \"F-score is\", len(true_sum))\n",
      "/home/pruthvish/JRF/RoadNetwork/RoadNetwork_VirtualEnv/lib/python3.8/site-packages/sklearn/metrics/_classification.py:1334: UndefinedMetricWarning: Precision is ill-defined and being set to 0.0 in labels with no predicted samples. Use `zero_division` parameter to control this behavior.\n",
      "  _warn_prf(average, modifier, msg_start, len(result))\n",
      "/home/pruthvish/JRF/RoadNetwork/RoadNetwork_VirtualEnv/lib/python3.8/site-packages/sklearn/metrics/_classification.py:1334: UndefinedMetricWarning: Recall is ill-defined and being set to 0.0 in labels with no true samples. Use `zero_division` parameter to control this behavior.\n",
      "  _warn_prf(average, modifier, msg_start, len(result))\n",
      "/home/pruthvish/JRF/RoadNetwork/RoadNetwork_VirtualEnv/lib/python3.8/site-packages/sklearn/metrics/_classification.py:1599: UndefinedMetricWarning: F-score is ill-defined and being set to 0.0 in labels with no true nor predicted samples. Use `zero_division` parameter to control this behavior.\n",
      "  _warn_prf(average, \"true nor predicted\", \"F-score is\", len(true_sum))\n",
      "/home/pruthvish/JRF/RoadNetwork/RoadNetwork_VirtualEnv/lib/python3.8/site-packages/sklearn/metrics/_classification.py:1334: UndefinedMetricWarning: Precision is ill-defined and being set to 0.0 in labels with no predicted samples. Use `zero_division` parameter to control this behavior.\n",
      "  _warn_prf(average, modifier, msg_start, len(result))\n",
      "/home/pruthvish/JRF/RoadNetwork/RoadNetwork_VirtualEnv/lib/python3.8/site-packages/sklearn/metrics/_classification.py:1334: UndefinedMetricWarning: Recall is ill-defined and being set to 0.0 in labels with no true samples. Use `zero_division` parameter to control this behavior.\n",
      "  _warn_prf(average, modifier, msg_start, len(result))\n",
      "/home/pruthvish/JRF/RoadNetwork/RoadNetwork_VirtualEnv/lib/python3.8/site-packages/sklearn/metrics/_classification.py:1599: UndefinedMetricWarning: F-score is ill-defined and being set to 0.0 in labels with no true nor predicted samples. Use `zero_division` parameter to control this behavior.\n",
      "  _warn_prf(average, \"true nor predicted\", \"F-score is\", len(true_sum))\n",
      "/home/pruthvish/JRF/RoadNetwork/RoadNetwork_VirtualEnv/lib/python3.8/site-packages/sklearn/metrics/_classification.py:1334: UndefinedMetricWarning: Precision is ill-defined and being set to 0.0 in labels with no predicted samples. Use `zero_division` parameter to control this behavior.\n",
      "  _warn_prf(average, modifier, msg_start, len(result))\n",
      "/home/pruthvish/JRF/RoadNetwork/RoadNetwork_VirtualEnv/lib/python3.8/site-packages/sklearn/metrics/_classification.py:1334: UndefinedMetricWarning: Recall is ill-defined and being set to 0.0 in labels with no true samples. Use `zero_division` parameter to control this behavior.\n",
      "  _warn_prf(average, modifier, msg_start, len(result))\n",
      "/home/pruthvish/JRF/RoadNetwork/RoadNetwork_VirtualEnv/lib/python3.8/site-packages/sklearn/metrics/_classification.py:1599: UndefinedMetricWarning: F-score is ill-defined and being set to 0.0 in labels with no true nor predicted samples. Use `zero_division` parameter to control this behavior.\n",
      "  _warn_prf(average, \"true nor predicted\", \"F-score is\", len(true_sum))\n",
      "/home/pruthvish/JRF/RoadNetwork/RoadNetwork_VirtualEnv/lib/python3.8/site-packages/sklearn/metrics/_classification.py:1334: UndefinedMetricWarning: Precision is ill-defined and being set to 0.0 in labels with no predicted samples. Use `zero_division` parameter to control this behavior.\n",
      "  _warn_prf(average, modifier, msg_start, len(result))\n",
      "/home/pruthvish/JRF/RoadNetwork/RoadNetwork_VirtualEnv/lib/python3.8/site-packages/sklearn/metrics/_classification.py:1334: UndefinedMetricWarning: Recall is ill-defined and being set to 0.0 in labels with no true samples. Use `zero_division` parameter to control this behavior.\n",
      "  _warn_prf(average, modifier, msg_start, len(result))\n",
      "/home/pruthvish/JRF/RoadNetwork/RoadNetwork_VirtualEnv/lib/python3.8/site-packages/sklearn/metrics/_classification.py:1599: UndefinedMetricWarning: F-score is ill-defined and being set to 0.0 in labels with no true nor predicted samples. Use `zero_division` parameter to control this behavior.\n",
      "  _warn_prf(average, \"true nor predicted\", \"F-score is\", len(true_sum))\n",
      "/home/pruthvish/JRF/RoadNetwork/RoadNetwork_VirtualEnv/lib/python3.8/site-packages/sklearn/metrics/_classification.py:1334: UndefinedMetricWarning: Precision is ill-defined and being set to 0.0 in labels with no predicted samples. Use `zero_division` parameter to control this behavior.\n",
      "  _warn_prf(average, modifier, msg_start, len(result))\n",
      "/home/pruthvish/JRF/RoadNetwork/RoadNetwork_VirtualEnv/lib/python3.8/site-packages/sklearn/metrics/_classification.py:1334: UndefinedMetricWarning: Recall is ill-defined and being set to 0.0 in labels with no true samples. Use `zero_division` parameter to control this behavior.\n",
      "  _warn_prf(average, modifier, msg_start, len(result))\n",
      "/home/pruthvish/JRF/RoadNetwork/RoadNetwork_VirtualEnv/lib/python3.8/site-packages/sklearn/metrics/_classification.py:1599: UndefinedMetricWarning: F-score is ill-defined and being set to 0.0 in labels with no true nor predicted samples. Use `zero_division` parameter to control this behavior.\n",
      "  _warn_prf(average, \"true nor predicted\", \"F-score is\", len(true_sum))\n",
      "/home/pruthvish/JRF/RoadNetwork/RoadNetwork_VirtualEnv/lib/python3.8/site-packages/sklearn/metrics/_classification.py:1334: UndefinedMetricWarning: Precision is ill-defined and being set to 0.0 in labels with no predicted samples. Use `zero_division` parameter to control this behavior.\n",
      "  _warn_prf(average, modifier, msg_start, len(result))\n",
      "/home/pruthvish/JRF/RoadNetwork/RoadNetwork_VirtualEnv/lib/python3.8/site-packages/sklearn/metrics/_classification.py:1334: UndefinedMetricWarning: Recall is ill-defined and being set to 0.0 in labels with no true samples. Use `zero_division` parameter to control this behavior.\n",
      "  _warn_prf(average, modifier, msg_start, len(result))\n",
      "/home/pruthvish/JRF/RoadNetwork/RoadNetwork_VirtualEnv/lib/python3.8/site-packages/sklearn/metrics/_classification.py:1599: UndefinedMetricWarning: F-score is ill-defined and being set to 0.0 in labels with no true nor predicted samples. Use `zero_division` parameter to control this behavior.\n",
      "  _warn_prf(average, \"true nor predicted\", \"F-score is\", len(true_sum))\n",
      "/home/pruthvish/JRF/RoadNetwork/RoadNetwork_VirtualEnv/lib/python3.8/site-packages/sklearn/metrics/_classification.py:1334: UndefinedMetricWarning: Precision is ill-defined and being set to 0.0 in labels with no predicted samples. Use `zero_division` parameter to control this behavior.\n",
      "  _warn_prf(average, modifier, msg_start, len(result))\n",
      "/home/pruthvish/JRF/RoadNetwork/RoadNetwork_VirtualEnv/lib/python3.8/site-packages/sklearn/metrics/_classification.py:1334: UndefinedMetricWarning: Recall is ill-defined and being set to 0.0 in labels with no true samples. Use `zero_division` parameter to control this behavior.\n",
      "  _warn_prf(average, modifier, msg_start, len(result))\n",
      "/home/pruthvish/JRF/RoadNetwork/RoadNetwork_VirtualEnv/lib/python3.8/site-packages/sklearn/metrics/_classification.py:1599: UndefinedMetricWarning: F-score is ill-defined and being set to 0.0 in labels with no true nor predicted samples. Use `zero_division` parameter to control this behavior.\n",
      "  _warn_prf(average, \"true nor predicted\", \"F-score is\", len(true_sum))\n"
     ]
    },
    {
     "name": "stderr",
     "output_type": "stream",
     "text": [
      "/home/pruthvish/JRF/RoadNetwork/RoadNetwork_VirtualEnv/lib/python3.8/site-packages/sklearn/metrics/_classification.py:1334: UndefinedMetricWarning: Precision is ill-defined and being set to 0.0 in labels with no predicted samples. Use `zero_division` parameter to control this behavior.\n",
      "  _warn_prf(average, modifier, msg_start, len(result))\n",
      "/home/pruthvish/JRF/RoadNetwork/RoadNetwork_VirtualEnv/lib/python3.8/site-packages/sklearn/metrics/_classification.py:1334: UndefinedMetricWarning: Recall is ill-defined and being set to 0.0 in labels with no true samples. Use `zero_division` parameter to control this behavior.\n",
      "  _warn_prf(average, modifier, msg_start, len(result))\n",
      "/home/pruthvish/JRF/RoadNetwork/RoadNetwork_VirtualEnv/lib/python3.8/site-packages/sklearn/metrics/_classification.py:1599: UndefinedMetricWarning: F-score is ill-defined and being set to 0.0 in labels with no true nor predicted samples. Use `zero_division` parameter to control this behavior.\n",
      "  _warn_prf(average, \"true nor predicted\", \"F-score is\", len(true_sum))\n",
      "/home/pruthvish/JRF/RoadNetwork/RoadNetwork_VirtualEnv/lib/python3.8/site-packages/sklearn/metrics/_classification.py:1334: UndefinedMetricWarning: Precision is ill-defined and being set to 0.0 in labels with no predicted samples. Use `zero_division` parameter to control this behavior.\n",
      "  _warn_prf(average, modifier, msg_start, len(result))\n",
      "/home/pruthvish/JRF/RoadNetwork/RoadNetwork_VirtualEnv/lib/python3.8/site-packages/sklearn/metrics/_classification.py:1334: UndefinedMetricWarning: Recall is ill-defined and being set to 0.0 in labels with no true samples. Use `zero_division` parameter to control this behavior.\n",
      "  _warn_prf(average, modifier, msg_start, len(result))\n",
      "/home/pruthvish/JRF/RoadNetwork/RoadNetwork_VirtualEnv/lib/python3.8/site-packages/sklearn/metrics/_classification.py:1599: UndefinedMetricWarning: F-score is ill-defined and being set to 0.0 in labels with no true nor predicted samples. Use `zero_division` parameter to control this behavior.\n",
      "  _warn_prf(average, \"true nor predicted\", \"F-score is\", len(true_sum))\n"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "Feature set-4\n"
     ]
    },
    {
     "name": "stderr",
     "output_type": "stream",
     "text": [
      "/home/pruthvish/JRF/RoadNetwork/RoadNetwork_VirtualEnv/lib/python3.8/site-packages/sklearn/metrics/_classification.py:1334: UndefinedMetricWarning: Precision is ill-defined and being set to 0.0 in labels with no predicted samples. Use `zero_division` parameter to control this behavior.\n",
      "  _warn_prf(average, modifier, msg_start, len(result))\n",
      "/home/pruthvish/JRF/RoadNetwork/RoadNetwork_VirtualEnv/lib/python3.8/site-packages/sklearn/metrics/_classification.py:1334: UndefinedMetricWarning: Recall is ill-defined and being set to 0.0 in labels with no true samples. Use `zero_division` parameter to control this behavior.\n",
      "  _warn_prf(average, modifier, msg_start, len(result))\n",
      "/home/pruthvish/JRF/RoadNetwork/RoadNetwork_VirtualEnv/lib/python3.8/site-packages/sklearn/metrics/_classification.py:1599: UndefinedMetricWarning: F-score is ill-defined and being set to 0.0 in labels with no true nor predicted samples. Use `zero_division` parameter to control this behavior.\n",
      "  _warn_prf(average, \"true nor predicted\", \"F-score is\", len(true_sum))\n",
      "/home/pruthvish/JRF/RoadNetwork/RoadNetwork_VirtualEnv/lib/python3.8/site-packages/sklearn/metrics/_classification.py:1334: UndefinedMetricWarning: Precision is ill-defined and being set to 0.0 in labels with no predicted samples. Use `zero_division` parameter to control this behavior.\n",
      "  _warn_prf(average, modifier, msg_start, len(result))\n",
      "/home/pruthvish/JRF/RoadNetwork/RoadNetwork_VirtualEnv/lib/python3.8/site-packages/sklearn/metrics/_classification.py:1334: UndefinedMetricWarning: Recall is ill-defined and being set to 0.0 in labels with no true samples. Use `zero_division` parameter to control this behavior.\n",
      "  _warn_prf(average, modifier, msg_start, len(result))\n",
      "/home/pruthvish/JRF/RoadNetwork/RoadNetwork_VirtualEnv/lib/python3.8/site-packages/sklearn/metrics/_classification.py:1599: UndefinedMetricWarning: F-score is ill-defined and being set to 0.0 in labels with no true nor predicted samples. Use `zero_division` parameter to control this behavior.\n",
      "  _warn_prf(average, \"true nor predicted\", \"F-score is\", len(true_sum))\n",
      "/home/pruthvish/JRF/RoadNetwork/RoadNetwork_VirtualEnv/lib/python3.8/site-packages/sklearn/metrics/_classification.py:1334: UndefinedMetricWarning: Precision is ill-defined and being set to 0.0 in labels with no predicted samples. Use `zero_division` parameter to control this behavior.\n",
      "  _warn_prf(average, modifier, msg_start, len(result))\n",
      "/home/pruthvish/JRF/RoadNetwork/RoadNetwork_VirtualEnv/lib/python3.8/site-packages/sklearn/metrics/_classification.py:1334: UndefinedMetricWarning: Recall is ill-defined and being set to 0.0 in labels with no true samples. Use `zero_division` parameter to control this behavior.\n",
      "  _warn_prf(average, modifier, msg_start, len(result))\n",
      "/home/pruthvish/JRF/RoadNetwork/RoadNetwork_VirtualEnv/lib/python3.8/site-packages/sklearn/metrics/_classification.py:1599: UndefinedMetricWarning: F-score is ill-defined and being set to 0.0 in labels with no true nor predicted samples. Use `zero_division` parameter to control this behavior.\n",
      "  _warn_prf(average, \"true nor predicted\", \"F-score is\", len(true_sum))\n",
      "/home/pruthvish/JRF/RoadNetwork/RoadNetwork_VirtualEnv/lib/python3.8/site-packages/sklearn/metrics/_classification.py:1334: UndefinedMetricWarning: Precision is ill-defined and being set to 0.0 in labels with no predicted samples. Use `zero_division` parameter to control this behavior.\n",
      "  _warn_prf(average, modifier, msg_start, len(result))\n",
      "/home/pruthvish/JRF/RoadNetwork/RoadNetwork_VirtualEnv/lib/python3.8/site-packages/sklearn/metrics/_classification.py:1334: UndefinedMetricWarning: Recall is ill-defined and being set to 0.0 in labels with no true samples. Use `zero_division` parameter to control this behavior.\n",
      "  _warn_prf(average, modifier, msg_start, len(result))\n",
      "/home/pruthvish/JRF/RoadNetwork/RoadNetwork_VirtualEnv/lib/python3.8/site-packages/sklearn/metrics/_classification.py:1599: UndefinedMetricWarning: F-score is ill-defined and being set to 0.0 in labels with no true nor predicted samples. Use `zero_division` parameter to control this behavior.\n",
      "  _warn_prf(average, \"true nor predicted\", \"F-score is\", len(true_sum))\n",
      "/home/pruthvish/JRF/RoadNetwork/RoadNetwork_VirtualEnv/lib/python3.8/site-packages/sklearn/metrics/_classification.py:1334: UndefinedMetricWarning: Precision is ill-defined and being set to 0.0 in labels with no predicted samples. Use `zero_division` parameter to control this behavior.\n",
      "  _warn_prf(average, modifier, msg_start, len(result))\n",
      "/home/pruthvish/JRF/RoadNetwork/RoadNetwork_VirtualEnv/lib/python3.8/site-packages/sklearn/metrics/_classification.py:1334: UndefinedMetricWarning: Recall is ill-defined and being set to 0.0 in labels with no true samples. Use `zero_division` parameter to control this behavior.\n",
      "  _warn_prf(average, modifier, msg_start, len(result))\n",
      "/home/pruthvish/JRF/RoadNetwork/RoadNetwork_VirtualEnv/lib/python3.8/site-packages/sklearn/metrics/_classification.py:1599: UndefinedMetricWarning: F-score is ill-defined and being set to 0.0 in labels with no true nor predicted samples. Use `zero_division` parameter to control this behavior.\n",
      "  _warn_prf(average, \"true nor predicted\", \"F-score is\", len(true_sum))\n",
      "/home/pruthvish/JRF/RoadNetwork/RoadNetwork_VirtualEnv/lib/python3.8/site-packages/sklearn/metrics/_classification.py:1334: UndefinedMetricWarning: Precision is ill-defined and being set to 0.0 in labels with no predicted samples. Use `zero_division` parameter to control this behavior.\n",
      "  _warn_prf(average, modifier, msg_start, len(result))\n",
      "/home/pruthvish/JRF/RoadNetwork/RoadNetwork_VirtualEnv/lib/python3.8/site-packages/sklearn/metrics/_classification.py:1334: UndefinedMetricWarning: Recall is ill-defined and being set to 0.0 in labels with no true samples. Use `zero_division` parameter to control this behavior.\n",
      "  _warn_prf(average, modifier, msg_start, len(result))\n",
      "/home/pruthvish/JRF/RoadNetwork/RoadNetwork_VirtualEnv/lib/python3.8/site-packages/sklearn/metrics/_classification.py:1599: UndefinedMetricWarning: F-score is ill-defined and being set to 0.0 in labels with no true nor predicted samples. Use `zero_division` parameter to control this behavior.\n",
      "  _warn_prf(average, \"true nor predicted\", \"F-score is\", len(true_sum))\n",
      "/home/pruthvish/JRF/RoadNetwork/RoadNetwork_VirtualEnv/lib/python3.8/site-packages/sklearn/metrics/_classification.py:1334: UndefinedMetricWarning: Precision is ill-defined and being set to 0.0 in labels with no predicted samples. Use `zero_division` parameter to control this behavior.\n",
      "  _warn_prf(average, modifier, msg_start, len(result))\n",
      "/home/pruthvish/JRF/RoadNetwork/RoadNetwork_VirtualEnv/lib/python3.8/site-packages/sklearn/metrics/_classification.py:1334: UndefinedMetricWarning: Recall is ill-defined and being set to 0.0 in labels with no true samples. Use `zero_division` parameter to control this behavior.\n",
      "  _warn_prf(average, modifier, msg_start, len(result))\n",
      "/home/pruthvish/JRF/RoadNetwork/RoadNetwork_VirtualEnv/lib/python3.8/site-packages/sklearn/metrics/_classification.py:1599: UndefinedMetricWarning: F-score is ill-defined and being set to 0.0 in labels with no true nor predicted samples. Use `zero_division` parameter to control this behavior.\n",
      "  _warn_prf(average, \"true nor predicted\", \"F-score is\", len(true_sum))\n",
      "/home/pruthvish/JRF/RoadNetwork/RoadNetwork_VirtualEnv/lib/python3.8/site-packages/sklearn/metrics/_classification.py:1334: UndefinedMetricWarning: Precision is ill-defined and being set to 0.0 in labels with no predicted samples. Use `zero_division` parameter to control this behavior.\n",
      "  _warn_prf(average, modifier, msg_start, len(result))\n",
      "/home/pruthvish/JRF/RoadNetwork/RoadNetwork_VirtualEnv/lib/python3.8/site-packages/sklearn/metrics/_classification.py:1334: UndefinedMetricWarning: Recall is ill-defined and being set to 0.0 in labels with no true samples. Use `zero_division` parameter to control this behavior.\n",
      "  _warn_prf(average, modifier, msg_start, len(result))\n",
      "/home/pruthvish/JRF/RoadNetwork/RoadNetwork_VirtualEnv/lib/python3.8/site-packages/sklearn/metrics/_classification.py:1599: UndefinedMetricWarning: F-score is ill-defined and being set to 0.0 in labels with no true nor predicted samples. Use `zero_division` parameter to control this behavior.\n",
      "  _warn_prf(average, \"true nor predicted\", \"F-score is\", len(true_sum))\n"
     ]
    },
    {
     "name": "stderr",
     "output_type": "stream",
     "text": [
      "/home/pruthvish/JRF/RoadNetwork/RoadNetwork_VirtualEnv/lib/python3.8/site-packages/sklearn/metrics/_classification.py:1334: UndefinedMetricWarning: Precision is ill-defined and being set to 0.0 in labels with no predicted samples. Use `zero_division` parameter to control this behavior.\n",
      "  _warn_prf(average, modifier, msg_start, len(result))\n",
      "/home/pruthvish/JRF/RoadNetwork/RoadNetwork_VirtualEnv/lib/python3.8/site-packages/sklearn/metrics/_classification.py:1334: UndefinedMetricWarning: Recall is ill-defined and being set to 0.0 in labels with no true samples. Use `zero_division` parameter to control this behavior.\n",
      "  _warn_prf(average, modifier, msg_start, len(result))\n",
      "/home/pruthvish/JRF/RoadNetwork/RoadNetwork_VirtualEnv/lib/python3.8/site-packages/sklearn/metrics/_classification.py:1599: UndefinedMetricWarning: F-score is ill-defined and being set to 0.0 in labels with no true nor predicted samples. Use `zero_division` parameter to control this behavior.\n",
      "  _warn_prf(average, \"true nor predicted\", \"F-score is\", len(true_sum))\n",
      "/home/pruthvish/JRF/RoadNetwork/RoadNetwork_VirtualEnv/lib/python3.8/site-packages/sklearn/metrics/_classification.py:1334: UndefinedMetricWarning: Precision is ill-defined and being set to 0.0 in labels with no predicted samples. Use `zero_division` parameter to control this behavior.\n",
      "  _warn_prf(average, modifier, msg_start, len(result))\n",
      "/home/pruthvish/JRF/RoadNetwork/RoadNetwork_VirtualEnv/lib/python3.8/site-packages/sklearn/metrics/_classification.py:1334: UndefinedMetricWarning: Recall is ill-defined and being set to 0.0 in labels with no true samples. Use `zero_division` parameter to control this behavior.\n",
      "  _warn_prf(average, modifier, msg_start, len(result))\n",
      "/home/pruthvish/JRF/RoadNetwork/RoadNetwork_VirtualEnv/lib/python3.8/site-packages/sklearn/metrics/_classification.py:1599: UndefinedMetricWarning: F-score is ill-defined and being set to 0.0 in labels with no true nor predicted samples. Use `zero_division` parameter to control this behavior.\n",
      "  _warn_prf(average, \"true nor predicted\", \"F-score is\", len(true_sum))\n"
     ]
    }
   ],
   "source": [
    "for Classifier, ClassifierName in zip(ClassifierList, ClassifierNameList):\n",
    "    print('Classifier, ClassifierName', Classifier, ClassifierName)\n",
    "    #for RecordType in ['.Raw', '.SegmentOtherThanStoppage']:\n",
    "\n",
    "    '''Feature set-1'''\n",
    "    FeatureType = '.HARFeature'\n",
    "    SelectedFeaturesFlag = False\n",
    "    SelectedFeatures = []\n",
    "\n",
    "    print('Feature set-1')\n",
    "    ClassifierName_ForModelSave = ClassifierName+\"_Set1\"\n",
    "    ApplyClassification(Classes, FeatureType, RecordType, SelectedFeatures, SelectedFeaturesFlag,\n",
    "                        Classifier, ClassifierName, ResultPathDir, ProjectDataUsed, RouteName,\n",
    "                        UsedPreTrained, ClassifierName_ForModelSave, TrainedModelPathDir, ReducedKFolds, \n",
    "                        NpPathDir, UseMongoDB\n",
    "                       )\n",
    "\n",
    "    '''Feature set-2'''\n",
    "    FeatureType = '.HARFeature'\n",
    "    SelectedFeaturesFlag = True\n",
    "    ClassifierName_ForModelSave = ClassifierName+\"_Set2\"\n",
    "    SelectedFeatures = CAC_Helper.SelectedFeaturesForFeatureType(FeatureType)\n",
    "\n",
    "    print('Feature set-2')\n",
    "\n",
    "    ApplyClassification(Classes, FeatureType, RecordType, SelectedFeatures, SelectedFeaturesFlag,\n",
    "                        Classifier, ClassifierName, ResultPathDir, ProjectDataUsed, RouteName, \n",
    "                        UsedPreTrained, ClassifierName_ForModelSave, TrainedModelPathDir, ReducedKFolds, \n",
    "                        NpPathDir, UseMongoDB\n",
    "                       )\n",
    "\n",
    "    '''Feature set-3'''\n",
    "    FeatureType = '.TransportFeatures'\n",
    "    SelectedFeatures = []\n",
    "    SelectedFeaturesFlag = False\n",
    "    print('Feature set-3')\n",
    "    ClassifierName_ForModelSave = ClassifierName+\"_Set3\"\n",
    "\n",
    "    ApplyClassification(Classes, FeatureType, RecordType, SelectedFeatures, SelectedFeaturesFlag,\n",
    "                        Classifier, ClassifierName, ResultPathDir, ProjectDataUsed, RouteName,\n",
    "                        UsedPreTrained, ClassifierName_ForModelSave, TrainedModelPathDir, ReducedKFolds, \n",
    "                        NpPathDir, UseMongoDB\n",
    "                       )   \n",
    "\n",
    "\n",
    "    '''Feature set-4'''\n",
    "    FeatureType = '.TransportFeatures'\n",
    "    SelectedFeatures = CAC_Helper.SelectedFeaturesForFeatureType(FeatureType)\n",
    "    SelectedFeaturesFlag = True\n",
    "\n",
    "    print('Feature set-4')\n",
    "    ClassifierName_ForModelSave = ClassifierName+\"_Set4\"\n",
    "    ApplyClassification(Classes, FeatureType, RecordType, SelectedFeatures, SelectedFeaturesFlag,\n",
    "                        Classifier, ClassifierName, ResultPathDir, ProjectDataUsed, RouteName,\n",
    "                        UsedPreTrained, ClassifierName_ForModelSave, TrainedModelPathDir, ReducedKFolds, \n",
    "                        NpPathDir, UseMongoDB\n",
    "                       )        \n",
    "\n"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 20,
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "Results for .Raw, .HARFeature, and selected features flag: False\n",
      "ConfusionMatrix \n",
      "[[467.   0.   0.   0.   0.]\n",
      " [  0.   0.   0.   0.   0.]\n",
      " [  0.   0.   0.   0.   0.]\n",
      " [  0.   0.   0. 169.  11.]\n",
      " [  1.   0.   0.  18. 179.]]\n",
      " \n",
      "PrecissionValue \n",
      "[0.99786325 0.         0.         0.90374332 0.94210526]\n",
      " \n",
      "RecallValue \n",
      "[1.         0.         0.         0.93888889 0.9040404 ]\n",
      " \n",
      "F1ScoreValue \n",
      "[0.99893048 0.         0.         0.92098093 0.92268041]\n",
      " \n",
      "AccuracyValue \n",
      "0.9644970414201184\n",
      " \n",
      "Results for .Raw, .HARFeature, and selected features flag: True\n",
      "ConfusionMatrix \n",
      "[[467.   0.   0.   0.   0.]\n",
      " [  0.   0.   0.   0.   0.]\n",
      " [  0.   0.   0.   0.   0.]\n",
      " [  0.   0.   0. 172.   8.]\n",
      " [  0.   0.   0.  20. 178.]]\n",
      " \n",
      "PrecissionValue \n",
      "[1.         0.         0.         0.89583333 0.95698925]\n",
      " \n",
      "RecallValue \n",
      "[1.         0.         0.         0.95555556 0.8989899 ]\n",
      " \n",
      "F1ScoreValue \n",
      "[1.         0.         0.         0.92473118 0.92708333]\n",
      " \n",
      "AccuracyValue \n",
      "0.9668639053254438\n",
      " \n",
      "Results for .Raw, .TransportFeatures, and selected features flag: False\n",
      "ConfusionMatrix \n",
      "[[467.   0.   0.   0.   0.]\n",
      " [  0.   0.   0.   0.   0.]\n",
      " [  0.   0.   0.   0.   0.]\n",
      " [  1.   0.   0. 167.  12.]\n",
      " [  1.   0.   0.   8. 189.]]\n",
      " \n",
      "PrecissionValue \n",
      "[0.99573561 0.         0.         0.95428571 0.94029851]\n",
      " \n",
      "RecallValue \n",
      "[1.         0.         0.         0.92777778 0.95454545]\n",
      " \n",
      "F1ScoreValue \n",
      "[0.99786325 0.         0.         0.94084507 0.94736842]\n",
      " \n",
      "AccuracyValue \n",
      "0.9739644970414201\n",
      " \n",
      "Results for .Raw, .TransportFeatures, and selected features flag: True\n",
      "ConfusionMatrix \n",
      "[[467.   0.   0.   0.   0.]\n",
      " [  0.   0.   0.   0.   0.]\n",
      " [  0.   0.   0.   0.   0.]\n",
      " [  1.   0.   0. 171.   8.]\n",
      " [  0.   0.   0.  19. 179.]]\n",
      " \n",
      "PrecissionValue \n",
      "[0.99786325 0.         0.         0.9        0.95721925]\n",
      " \n",
      "RecallValue \n",
      "[1.        0.        0.        0.95      0.9040404]\n",
      " \n",
      "F1ScoreValue \n",
      "[0.99893048 0.         0.         0.92432432 0.92987013]\n",
      " \n",
      "AccuracyValue \n",
      "0.9668639053254438\n",
      " \n",
      "Results for .Raw, .HARFeature, and selected features flag: False\n",
      "ConfusionMatrix \n",
      "[[4.668e+03 0.000e+00 0.000e+00 0.000e+00 0.000e+00]\n",
      " [0.000e+00 0.000e+00 0.000e+00 0.000e+00 0.000e+00]\n",
      " [0.000e+00 0.000e+00 0.000e+00 0.000e+00 0.000e+00]\n",
      " [3.000e+00 0.000e+00 0.000e+00 1.523e+03 2.710e+02]\n",
      " [2.000e+00 0.000e+00 0.000e+00 2.620e+02 1.713e+03]]\n",
      " \n",
      "PrecissionValue \n",
      "[0.99893162 0.         0.         0.85604504 0.86388957]\n",
      " \n",
      "RecallValue \n",
      "[1.         0.         0.         0.84747052 0.86640004]\n",
      " \n",
      "F1ScoreValue \n",
      "[0.99946524 0.         0.         0.85073667 0.8643697 ]\n",
      " \n",
      "AccuracyValue \n",
      "0.9362667208839281\n",
      " \n",
      "Results for .Raw, .HARFeature, and selected features flag: True\n",
      "ConfusionMatrix \n",
      "[[4.668e+03 0.000e+00 0.000e+00 0.000e+00 0.000e+00]\n",
      " [0.000e+00 0.000e+00 0.000e+00 0.000e+00 0.000e+00]\n",
      " [0.000e+00 0.000e+00 0.000e+00 0.000e+00 0.000e+00]\n",
      " [4.000e+00 0.000e+00 0.000e+00 1.507e+03 2.860e+02]\n",
      " [3.000e+00 0.000e+00 0.000e+00 2.620e+02 1.712e+03]]\n",
      " \n",
      "PrecissionValue \n",
      "[0.99850791 0.         0.         0.85505239 0.85798841]\n",
      " \n",
      "RecallValue \n",
      "[1.         0.         0.         0.83854749 0.86590268]\n",
      " \n",
      "F1ScoreValue \n",
      "[0.99925225 0.         0.         0.84536249 0.86096787]\n",
      " \n",
      "AccuracyValue \n",
      "0.9342523626573935\n",
      " \n",
      "Results for .Raw, .TransportFeatures, and selected features flag: False\n",
      "ConfusionMatrix \n",
      "[[4.668e+03 0.000e+00 0.000e+00 0.000e+00 0.000e+00]\n",
      " [0.000e+00 0.000e+00 0.000e+00 0.000e+00 0.000e+00]\n",
      " [0.000e+00 0.000e+00 0.000e+00 0.000e+00 0.000e+00]\n",
      " [2.000e+00 0.000e+00 0.000e+00 1.550e+03 2.450e+02]\n",
      " [4.000e+00 0.000e+00 0.000e+00 1.100e+02 1.863e+03]]\n",
      " \n",
      "PrecissionValue \n",
      "[0.99871931 0.         0.         0.93399167 0.88967268]\n",
      " \n",
      "RecallValue \n",
      "[1.         0.         0.         0.86260087 0.94230118]\n",
      " \n",
      "F1ScoreValue \n",
      "[0.99935852 0.         0.         0.89392584 0.91351202]\n",
      " \n",
      "AccuracyValue \n",
      "0.9572347794385708\n",
      " \n",
      "Results for .Raw, .TransportFeatures, and selected features flag: True\n",
      "ConfusionMatrix \n",
      "[[4.668e+03 0.000e+00 0.000e+00 0.000e+00 0.000e+00]\n",
      " [0.000e+00 0.000e+00 0.000e+00 0.000e+00 0.000e+00]\n",
      " [0.000e+00 0.000e+00 0.000e+00 0.000e+00 0.000e+00]\n",
      " [3.000e+00 0.000e+00 0.000e+00 1.515e+03 2.790e+02]\n",
      " [2.000e+00 0.000e+00 0.000e+00 2.760e+02 1.699e+03]]\n",
      " \n",
      "PrecissionValue \n",
      "[0.99893117 0.         0.         0.84926891 0.85939022]\n",
      " \n",
      "RecallValue \n",
      "[1.         0.         0.         0.84301986 0.85931908]\n",
      " \n",
      "F1ScoreValue \n",
      "[0.99946501 0.         0.         0.84499994 0.8584157 ]\n",
      " \n",
      "AccuracyValue \n",
      "0.9336586836422782\n",
      " \n",
      "\n"
     ]
    }
   ],
   "source": [
    "'''Read the value for one of the machine learning algorithm'''\n",
    "file = os.path.join(ResultPathDir,f'{ClassifierName}.txt')\n",
    "f = open(file, \"r\")\n",
    "print(f.read())"
   ]
  }
 ],
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