In this unit, we describe the procedure for training the stepping detector. Further, we present the classification result for stepping detector.

Stepping detector

'''Import and initialize MongoClient'''
import subprocess
import os
import sys
import json
from pymongo import     MongoClient

con = MongoClient()

import pprint
import numpy as np
from pathlib import Path

'''Import project specific library'''
sys.path.append(os.path.join(os.getcwd(), 'LibCode'))
import HAR_OrientetionIndependence
import HARSaveToMongo
import ComputeFeaturesTransportMode
import FeaturesExtraction

'''For updating the lib changes effects'''
import importlib
importlib.reload(HAR_OrientetionIndependence)
importlib.reload(HARSaveToMongo)
importlib.reload(ComputeFeaturesTransportMode)
importlib.reload(FeaturesExtraction)

<module 'FeaturesExtraction' from '/home/pruthvish/JRF/GitVersion_APTS_Software_Np/code/LibCode/FeaturesExtraction.py'>

Save in MongoDB

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.

Decomposition of accelerometer data

The accelerometer record data is decomposed to horizontal and vertical components with the IntervalLength of 140 points.

def HAR_OrientetionIndependenceFunction(RouteName, IntervalLength):

    '''
    input: The route name and dataset directory name

    output: None

    function: It fetches the data records placed in the specified data set directory
    and save them in the MongoDB database. The function also computes the vertical and
    horizontal accelerometer components and saves them in the MongoDB database.
    '''

    SingleTripsInfo = [LR['SingleTripInfo'] for LR in
                       con[RouteName]['TripsInfo'].find({'ConvertedToEarthAxis':False})]

    SingleTripsInfo = HAR_OrientetionIndependence.GetSingleTripRecord(SingleTripsInfo)

    for (index,SingleTripInfo) in enumerate(SingleTripsInfo):
        AcclMagRecordsListStoppages =[AclR for AclR in
                                      con[RouteName][f'acc.{SingleTripInfo}.Raw'].find().sort([('index',1)])]
        '''
        print(AcclMagRecordsListStoppages)
        input()
        '''

        HAR_OrientetionIndependence.ProcessEarthaxisHVComponentUsingJigSawMethod(
            RouteName,SingleTripInfo, AcclMagRecordsListStoppages, IntervalLength)

        print('Converting the accelerometer data to orientation independent record for SingleTripInfo')
        print(SingleTripInfo)
        con[RouteName]['TripsInfo'].update_one({'SingleTripInfo':f'acc.{SingleTripInfo}'},
                                               {'$set':{'ConvertedToEarthAxis':True}})

    #input()
    #'''

Features Extraction

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.

def ComputeFeatures(RouteName, WindowList, WindowIndex, RecordType):

    '''
    input: The WindowList and WindowIndex specify the window size for feature computation,
    record type (Raw or Segment other than stoppage segment), and route name.

    output: None

    function: It extracts the appropriate accelerometer components from the MongoDB database based
    on the provided input and computes the features on the windowed accelerometer component. The
    computed features are stored in the MongoDB database.
    '''

    SingleTripsInfo = [LR['SingleTripInfo'] for LR in
                       con[RouteName]['TripsInfo'].find({'ConvertedToEarthAxis':True})]

    SingleTripsInfo = HAR_OrientetionIndependence.GetSingleTripRecord(SingleTripsInfo)

    for (index,SingleTripInfo) in enumerate(SingleTripsInfo):
        HVComponent =[AclR for AclR in
                      con[RouteName][SingleTripInfo+'.EAccHVComponent'].find(
                      ).sort([('index',1)])]
        ModeIntList = SingleTripInfo.split('.')
        ModeInt = ActivityIncluded.index(ModeIntList[0])
        #print(ModeIntList)
        #input()
        #'''
        ComputeFeaturesTransportMode.ComputeFeature(SingleTripInfo,HVComponent,ModeInt,WindowList[WindowIndex],
                                                    RecordType, RouteName)

        FeaturesExtraction.ComputeFeatureForComponents(RouteName,HVComponent,ModeInt,
                                                       WindowList[WindowIndex],SingleTripInfo,RecordType)
        #'''
        #print(SingleTripInfo)
        #print(ModeInt)
        print(SingleTripInfo)
        #pprint.pprint(AcclMagRecordsListStoppages)
        #input()

def LoadInMongoFromNp(RouteName, NpPathDir):

    '''
    input: The route name and numpy directory path
    output: The MongoDB database collections from the Numpy files
    function: It creates the MongoDB database of TripsInfo collections
    and features collections from the Numpy files.
    '''

    CollectionName = 'TripsInfo'
    TripsInfoRecords = np.load(f'{NpPathDir}/{RouteName}/{CollectionName}.npy', allow_pickle=True)

    print('Saving data in mongoDB')
    print(RouteName, CollectionName)
    con[RouteName][CollectionName].insert_many(TripsInfoRecords.tolist())

    CollectionNames = os.listdir(f'{NpPathDir}/{RouteName}')
    #print(CollectionNames)

    CollectionNames_1 = [rec for rec in CollectionNames if '\'.' not in rec] # To address the error
    CollectionNames_2 = [rec for rec in CollectionNames if 'Feature' in rec]

    #print('Saving data in mongoDB')
    for Collection in CollectionNames_2:
        RecordsList = np.load(f'{NpPathDir}/{RouteName}/{Collection}', allow_pickle=True)
        #print(Collection)
        #pprint.pprint(RecordsList[0:3])

        CollectionName = Collection[0:-4]

        print(RouteName, CollectionName)
        con[RouteName][CollectionName].insert_many(RecordsList.tolist())



def SaveInNp(RouteName, NpPathDir):

    '''
    input: The route name and numpy directory path
    output: Numpy files of the MongoDB database
    function: It stores the Numpy files for the MongoDB database in the specified directory path
    '''

    CollectionNames = [Collection for Collection in
                        con[RouteName].list_collection_names() if Collection!='system.indexes']

    for CollectionName in CollectionNames:
        print('CollectionName', CollectionName)
        RecordsList = [rec for rec in con[RouteName][CollectionName].find().sort([('_id',1)])]

        for RecordDict in RecordsList:
            del[RecordDict['_id']]

        if os.path.exists(os.path.join(NpPathDir, RouteName)) == False:
            os.mkdir(os.path.join(NpPathDir, RouteName))


        #np.save(f'{Path}/{Database}/{CollectionName}.npy', RecordsList)
        np.save(os.path.join(NpPathDir, RouteName,f'{CollectionName}.npy'), RecordsList)

'''For directory management'''
path = Path(os.getcwd())
OneLevelUpPath = path.parents[0]

'''Path for Np'''
NpPathDir = os.path.join(str(OneLevelUpPath), 'data','NpData')

Variables

ProjectDataUsed: determines whether the project data or the user’s own data is used for execution.

UsedPreTrained: determines whether the pretrained and precomputed dataset or raw data is used for execution.

UseMongoDB: determines whether the MonngoDB database or Numpy file is used for execution.

ReducedKFolds: If false: one fold is used, else ten-fold is used

'''
ProjectDataUsed = True
UsedPreTrained = True
ReducedKFolds = False
UseMongoDB = True
'''

#'''
ProjectDataUsed = True
UsedPreTrained = True
ReducedKFolds = True
UseMongoDB = False
#'''

'''
ProjectDataUsed = True
UsedPreTrained = False
ReducedKFolds = False
UseMongoDB = False
'''

'''Variable initialization'''
RouteName = 'Demo_HAR_DATASET_Preprocessing_And_HV'
if ProjectDataUsed==True:
    RecordDir = os.path.join(str(OneLevelUpPath), 'data','HAPTDataSet','RawData','')
else:
    RecordDir = os.path.join(str(OneLevelUpPath), 'data','UserData','HAPTDataSet','RawData','')
IntervalLength = 140
RecordType = '.Raw'

WindowList = [32,64,128,256,512]
WindowIndex = 2
Activties = ['WALKING', 'WALKING_UPSTAIRS','WALKING_DOWNSTAIRS','SITTING','STANDING','LAYING',
            'STAND_TO_SIT','SIT_TO_STAND','SIT_TO_LIE','LIE_TO_SIT','STAND_TO_LIE','LIE_TO_STAND']
ActivityID = [1,2,3,4,5,6,7,8,9,10,11,12]
ActivityIncluded = ['WALKING', 'WALKING_UPSTAIRS','WALKING_DOWNSTAIRS','SITTING','STANDING','LAYING',
            'STAND_TO_SIT','SIT_TO_STAND','SIT_TO_LIE','LIE_TO_SIT','STAND_TO_LIE','LIE_TO_STAND']
ActivityIncludedClassInt = [0,1,2,3,4]

if UsedPreTrained==False and UseMongoDB==True:

    print('Reading data and saving in MongoDB')
    HARSaveToMongo.SaveHARDataInMongo(RouteName, RecordDir)
    print(f'Computing preprocessing for {RecordType} segments')
    HAR_OrientetionIndependenceFunction(RouteName, IntervalLength)
    print(f'Computing features for {RecordType} segments')
    ComputeFeatures(RouteName, WindowList, WindowIndex, RecordType)


    print('Saving MongoData in Np files')
    SaveInNp(RouteName, NpPathDir)


elif UseMongoDB==True:
    RouteNamesListInDB = con.list_database_names()
    if RouteName not in RouteNamesListInDB:
        '''Load the data for RouteName, if RouteName is not in RouteNamesList'''
        print('Loading MongoData from Np files')
        LoadInMongoFromNp(RouteName, NpPathDir)

#con.drop_database(RouteName)

Classification

'''Import Libs'''
from sklearn.model_selection import StratifiedKFold
from sklearn.metrics import accuracy_score, confusion_matrix,precision_score, recall_score, f1_score
from sklearn import tree
from sklearn.svm import SVC
from sklearn.preprocessing import StandardScaler
from sklearn.ensemble import RandomForestClassifier
from sklearn.linear_model import LogisticRegression
from sklearn.naive_bayes import GaussianNB
from collections import Counter
from sklearn.impute import SimpleImputer

'''Custom library'''
import CAC_Helper
import Stepper_Helper

'''For updating the lib changes effects'''
import importlib
importlib.reload(CAC_Helper)
importlib.reload(Stepper_Helper)

<module 'Stepper_Helper' from '/home/pruthvish/JRF/GitVersion_APTS_Software_Np/code/LibCode/Stepper_Helper.py'>

'''Variables for Classification'''
ResultPathDir = os.path.join(str(OneLevelUpPath), 'results','SteppingDetector','')


if os.path.exists(ResultPathDir) == False:
    os.mkdir(ResultPathDir)

TrainedModelPathDir = os.path.join(str(OneLevelUpPath), 'data', 'TrainedModel','SteppingDetector','')

'''Any one route type as decided by Stoppage experiment'''
#RecordType = '.SegmentOtherThanStoppage'
#RecordType = '.StoppageSegment'
RecordType = '.Raw'

ClassifierList = [GaussianNB(), LogisticRegression(random_state=0),
                  RandomForestClassifier(max_depth=20), tree.DecisionTreeClassifier(),
                  SVC(gamma='auto')
                 ]
ClassifierNameList = ['NB', 'LogisticRegression', 'RF', 'DT', 'SVC']

Index = 3

Classifier = ClassifierList[Index]
ClassifierName = ClassifierNameList[Index]

def ApplyClassification(Classes, FeatureType, RecordType, SelectedFeatures, SelectedFeaturesFlag,
                        Classifier, ClassifierName, ResultPathDir, ProjectDataUsed, RouteName,
                        UsedPreTrained, ClassifierName_ForModelSave, TrainedModelPathDir, ReducedKFolds,
                        NpPathDir, UseMongoDB
                       ):

    '''
    input:
        Classes: The number of classes

        FeatureType and RecordType: feature type and record type information

        SelectedFeatures and SelectedFeaturesFlag: selected features list and flag to
        determine if selected features are list is used

        Classifier and ClassifierName: classifier object variable and classifier name

        ResultPathDir: path of result directory

        ProjectDataUsed: flag to determine whether the project dataset or user dataset is used

        RouteNameTestList: The route names list to be considered during classification

        UsedPreTrained: Flag to determine whether the pretrained classifier should be used
        or the classifier is to be trained

        ClassifierName_ForModelSave: the name of classifier for saving a model

        TrainedModelPathDir: path of trainedModel directory

    output: None

    function: It trains and validates the classifier the ten-fold cross-validation with stratified
    sampling of each class. The performance metrics of the classifier is stores as a txt file in the
    result directory

    '''

    MetricsDict = CAC_Helper.InitializeMetricsDict(Classes)

    #SelectedFeatures = []

    if UseMongoDB==True:
        #X, y = Stepper_Helper.GetFeaturesFromMongoDB(RouteName, FeatureType, RecordType)
        X, y = Stepper_Helper.GetFeaturesFromMongoDB(RouteName, FeatureType, RecordType,
                                                     SelectedFeatures, SelectedFeaturesFlag)


        if os.path.exists(os.path.join(NpPathDir,'SteppingDetector'))==False:
            os.mkdir(os.path.join(NpPathDir,'SteppingDetector'))

        np.save(f'{NpPathDir}/SteppingDetector/X_{FeatureType}_{RecordType}_{SelectedFeaturesFlag}.npy', X)
        np.save(f'{NpPathDir}/SteppingDetector/y_{FeatureType}_{RecordType}_{SelectedFeaturesFlag}.npy', y)

    else:
        X = np.load(f'{NpPathDir}/SteppingDetector/X_{FeatureType}_{RecordType}_{SelectedFeaturesFlag}.npy',
                    allow_pickle=True)
        y = np.load(f'{NpPathDir}/SteppingDetector/y_{FeatureType}_{RecordType}_{SelectedFeaturesFlag}.npy',
                    allow_pickle=True)


    MetricsDict = CAC_Helper.TrainAndPredict(X, y, Classifier, MetricsDict, ResultPathDir,
                                             ClassifierName, UsedPreTrained,
                                             ClassifierName_ForModelSave, TrainedModelPathDir, ReducedKFolds)

    CAC_Helper.PrintMetricsDict(ClassifierName, ResultPathDir, FeatureType, RecordType,
                                SelectedFeaturesFlag, MetricsDict)

Classes = 5

for Classifier, ClassifierName in zip(ClassifierList, ClassifierNameList):
    print('Classifier, ClassifierName', Classifier, ClassifierName)
    #for RecordType in ['.Raw', '.SegmentOtherThanStoppage']:

    '''Feature set-1'''
    FeatureType = '.HARFeature'
    SelectedFeaturesFlag = False
    SelectedFeatures = []

    print('Feature set-1')
    ClassifierName_ForModelSave = ClassifierName+"_Set1"
    ApplyClassification(Classes, FeatureType, RecordType, SelectedFeatures, SelectedFeaturesFlag,
                        Classifier, ClassifierName, ResultPathDir, ProjectDataUsed, RouteName,
                        UsedPreTrained, ClassifierName_ForModelSave, TrainedModelPathDir, ReducedKFolds,
                        NpPathDir, UseMongoDB
                       )

    '''Feature set-2'''
    FeatureType = '.HARFeature'
    SelectedFeaturesFlag = True
    ClassifierName_ForModelSave = ClassifierName+"_Set2"
    SelectedFeatures = CAC_Helper.SelectedFeaturesForFeatureType(FeatureType)

    print('Feature set-2')

    ApplyClassification(Classes, FeatureType, RecordType, SelectedFeatures, SelectedFeaturesFlag,
                        Classifier, ClassifierName, ResultPathDir, ProjectDataUsed, RouteName,
                        UsedPreTrained, ClassifierName_ForModelSave, TrainedModelPathDir, ReducedKFolds,
                        NpPathDir, UseMongoDB
                       )

    '''Feature set-3'''
    FeatureType = '.TransportFeatures'
    SelectedFeatures = []
    SelectedFeaturesFlag = False
    print('Feature set-3')
    ClassifierName_ForModelSave = ClassifierName+"_Set3"

    ApplyClassification(Classes, FeatureType, RecordType, SelectedFeatures, SelectedFeaturesFlag,
                        Classifier, ClassifierName, ResultPathDir, ProjectDataUsed, RouteName,
                        UsedPreTrained, ClassifierName_ForModelSave, TrainedModelPathDir, ReducedKFolds,
                        NpPathDir, UseMongoDB
                       )


    '''Feature set-4'''
    FeatureType = '.TransportFeatures'
    SelectedFeatures = CAC_Helper.SelectedFeaturesForFeatureType(FeatureType)
    SelectedFeaturesFlag = True

    print('Feature set-4')
    ClassifierName_ForModelSave = ClassifierName+"_Set4"
    ApplyClassification(Classes, FeatureType, RecordType, SelectedFeatures, SelectedFeaturesFlag,
                        Classifier, ClassifierName, ResultPathDir, ProjectDataUsed, RouteName,
                        UsedPreTrained, ClassifierName_ForModelSave, TrainedModelPathDir, ReducedKFolds,
                        NpPathDir, UseMongoDB
                       )

Classifier, ClassifierName GaussianNB() NB
Feature set-1

/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.
  _warn_prf(average, modifier, msg_start, len(result))
/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.
  _warn_prf(average, modifier, msg_start, len(result))
/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.
  _warn_prf(average, "true nor predicted", "F-score is", len(true_sum))
/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.
  _warn_prf(average, modifier, msg_start, len(result))
/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.
  _warn_prf(average, modifier, msg_start, len(result))
/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.
  _warn_prf(average, "true nor predicted", "F-score is", len(true_sum))
/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.
  _warn_prf(average, modifier, msg_start, len(result))
/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.
  _warn_prf(average, modifier, msg_start, len(result))
/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.
  _warn_prf(average, "true nor predicted", "F-score is", len(true_sum))
/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.
  _warn_prf(average, modifier, msg_start, len(result))
/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.
  _warn_prf(average, modifier, msg_start, len(result))
/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.
  _warn_prf(average, "true nor predicted", "F-score is", len(true_sum))
/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.
  _warn_prf(average, modifier, msg_start, len(result))
/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.
  _warn_prf(average, modifier, msg_start, len(result))
/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.
  _warn_prf(average, "true nor predicted", "F-score is", len(true_sum))
/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.
  _warn_prf(average, modifier, msg_start, len(result))
/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.
  _warn_prf(average, modifier, msg_start, len(result))
/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.
  _warn_prf(average, "true nor predicted", "F-score is", len(true_sum))
/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.
  _warn_prf(average, modifier, msg_start, len(result))
/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.
  _warn_prf(average, modifier, msg_start, len(result))
/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.
  _warn_prf(average, "true nor predicted", "F-score is", len(true_sum))
/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.
  _warn_prf(average, modifier, msg_start, len(result))
/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.
  _warn_prf(average, modifier, msg_start, len(result))
/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.
  _warn_prf(average, "true nor predicted", "F-score is", len(true_sum))
/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.
  _warn_prf(average, modifier, msg_start, len(result))
/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.
  _warn_prf(average, modifier, msg_start, len(result))
/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.
  _warn_prf(average, "true nor predicted", "F-score is", len(true_sum))
/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.
  _warn_prf(average, modifier, msg_start, len(result))
/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.
  _warn_prf(average, modifier, msg_start, len(result))
/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.
  _warn_prf(average, "true nor predicted", "F-score is", len(true_sum))

Feature set-2

/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.
  _warn_prf(average, modifier, msg_start, len(result))
/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.
  _warn_prf(average, modifier, msg_start, len(result))
/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.
  _warn_prf(average, "true nor predicted", "F-score is", len(true_sum))
/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.
  _warn_prf(average, modifier, msg_start, len(result))
/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.
  _warn_prf(average, modifier, msg_start, len(result))
/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.
  _warn_prf(average, "true nor predicted", "F-score is", len(true_sum))
/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.
  _warn_prf(average, modifier, msg_start, len(result))
/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.
  _warn_prf(average, modifier, msg_start, len(result))
/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.
  _warn_prf(average, "true nor predicted", "F-score is", len(true_sum))
/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.
  _warn_prf(average, modifier, msg_start, len(result))
/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.
  _warn_prf(average, modifier, msg_start, len(result))
/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.
  _warn_prf(average, "true nor predicted", "F-score is", len(true_sum))
/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.
  _warn_prf(average, modifier, msg_start, len(result))
/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.
  _warn_prf(average, modifier, msg_start, len(result))
/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.
  _warn_prf(average, "true nor predicted", "F-score is", len(true_sum))
/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.
  _warn_prf(average, modifier, msg_start, len(result))
/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.
  _warn_prf(average, modifier, msg_start, len(result))
/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.
  _warn_prf(average, "true nor predicted", "F-score is", len(true_sum))
/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.
  _warn_prf(average, modifier, msg_start, len(result))
/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.
  _warn_prf(average, modifier, msg_start, len(result))
/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.
  _warn_prf(average, "true nor predicted", "F-score is", len(true_sum))
/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.
  _warn_prf(average, modifier, msg_start, len(result))
/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.
  _warn_prf(average, modifier, msg_start, len(result))
/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.
  _warn_prf(average, "true nor predicted", "F-score is", len(true_sum))
/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.
  _warn_prf(average, modifier, msg_start, len(result))
/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.
  _warn_prf(average, modifier, msg_start, len(result))
/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.
  _warn_prf(average, "true nor predicted", "F-score is", len(true_sum))
/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.
  _warn_prf(average, modifier, msg_start, len(result))
/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.
  _warn_prf(average, modifier, msg_start, len(result))
/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.
  _warn_prf(average, "true nor predicted", "F-score is", len(true_sum))

Feature set-3

/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.
  _warn_prf(average, modifier, msg_start, len(result))
/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.
  _warn_prf(average, modifier, msg_start, len(result))
/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.
  _warn_prf(average, "true nor predicted", "F-score is", len(true_sum))
/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.
  _warn_prf(average, modifier, msg_start, len(result))
/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.
  _warn_prf(average, modifier, msg_start, len(result))
/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.
  _warn_prf(average, "true nor predicted", "F-score is", len(true_sum))
/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.
  _warn_prf(average, modifier, msg_start, len(result))
/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.
  _warn_prf(average, modifier, msg_start, len(result))
/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.
  _warn_prf(average, "true nor predicted", "F-score is", len(true_sum))
/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.
  _warn_prf(average, modifier, msg_start, len(result))
/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.
  _warn_prf(average, modifier, msg_start, len(result))
/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.
  _warn_prf(average, "true nor predicted", "F-score is", len(true_sum))
/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.
  _warn_prf(average, modifier, msg_start, len(result))
/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.
  _warn_prf(average, modifier, msg_start, len(result))
/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.
  _warn_prf(average, "true nor predicted", "F-score is", len(true_sum))
/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.
  _warn_prf(average, modifier, msg_start, len(result))
/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.
  _warn_prf(average, modifier, msg_start, len(result))
/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.
  _warn_prf(average, "true nor predicted", "F-score is", len(true_sum))
/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.
  _warn_prf(average, modifier, msg_start, len(result))
/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.
  _warn_prf(average, modifier, msg_start, len(result))
/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.
  _warn_prf(average, "true nor predicted", "F-score is", len(true_sum))
/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.
  _warn_prf(average, modifier, msg_start, len(result))
/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.
  _warn_prf(average, modifier, msg_start, len(result))
/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.
  _warn_prf(average, "true nor predicted", "F-score is", len(true_sum))
/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.
  _warn_prf(average, modifier, msg_start, len(result))
/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.
  _warn_prf(average, modifier, msg_start, len(result))
/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.
  _warn_prf(average, "true nor predicted", "F-score is", len(true_sum))
/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.
  _warn_prf(average, modifier, msg_start, len(result))
/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.
  _warn_prf(average, modifier, msg_start, len(result))
/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.
  _warn_prf(average, "true nor predicted", "F-score is", len(true_sum))

Feature set-4
Classifier, ClassifierName LogisticRegression(random_state=0) LogisticRegression
Feature set-1

/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.
  _warn_prf(average, modifier, msg_start, len(result))
/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.
  _warn_prf(average, modifier, msg_start, len(result))
/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.
  _warn_prf(average, "true nor predicted", "F-score is", len(true_sum))
/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.
  _warn_prf(average, modifier, msg_start, len(result))
/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.
  _warn_prf(average, modifier, msg_start, len(result))
/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.
  _warn_prf(average, "true nor predicted", "F-score is", len(true_sum))
/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.
  _warn_prf(average, modifier, msg_start, len(result))
/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.
  _warn_prf(average, modifier, msg_start, len(result))
/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.
  _warn_prf(average, "true nor predicted", "F-score is", len(true_sum))
/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.
  _warn_prf(average, modifier, msg_start, len(result))
/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.
  _warn_prf(average, modifier, msg_start, len(result))
/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.
  _warn_prf(average, "true nor predicted", "F-score is", len(true_sum))
/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.
  _warn_prf(average, modifier, msg_start, len(result))
/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.
  _warn_prf(average, modifier, msg_start, len(result))
/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.
  _warn_prf(average, "true nor predicted", "F-score is", len(true_sum))
/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.
  _warn_prf(average, modifier, msg_start, len(result))
/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.
  _warn_prf(average, modifier, msg_start, len(result))
/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.
  _warn_prf(average, "true nor predicted", "F-score is", len(true_sum))
/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.
  _warn_prf(average, modifier, msg_start, len(result))
/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.
  _warn_prf(average, modifier, msg_start, len(result))
/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.
  _warn_prf(average, "true nor predicted", "F-score is", len(true_sum))
/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.
  _warn_prf(average, modifier, msg_start, len(result))
/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.
  _warn_prf(average, modifier, msg_start, len(result))
/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.
  _warn_prf(average, "true nor predicted", "F-score is", len(true_sum))
/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.
  _warn_prf(average, modifier, msg_start, len(result))
/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.
  _warn_prf(average, modifier, msg_start, len(result))
/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.
  _warn_prf(average, "true nor predicted", "F-score is", len(true_sum))
/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.
  _warn_prf(average, modifier, msg_start, len(result))
/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.
  _warn_prf(average, modifier, msg_start, len(result))
/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.
  _warn_prf(average, "true nor predicted", "F-score is", len(true_sum))
/home/pruthvish/JRF/RoadNetwork/RoadNetwork_VirtualEnv/lib/python3.8/site-packages/sklearn/linear_model/_logistic.py:444: ConvergenceWarning: lbfgs failed to converge (status=1):
STOP: TOTAL NO. of ITERATIONS REACHED LIMIT.

Increase the number of iterations (max_iter) or scale the data as shown in:
    https://scikit-learn.org/stable/modules/preprocessing.html
Please also refer to the documentation for alternative solver options:
    https://scikit-learn.org/stable/modules/linear_model.html#logistic-regression
  n_iter_i = _check_optimize_result(
/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.
  _warn_prf(average, modifier, msg_start, len(result))
/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.
  _warn_prf(average, modifier, msg_start, len(result))
/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.
  _warn_prf(average, "true nor predicted", "F-score is", len(true_sum))
/home/pruthvish/JRF/RoadNetwork/RoadNetwork_VirtualEnv/lib/python3.8/site-packages/sklearn/linear_model/_logistic.py:444: ConvergenceWarning: lbfgs failed to converge (status=1):
STOP: TOTAL NO. of ITERATIONS REACHED LIMIT.

Increase the number of iterations (max_iter) or scale the data as shown in:
    https://scikit-learn.org/stable/modules/preprocessing.html
Please also refer to the documentation for alternative solver options:
    https://scikit-learn.org/stable/modules/linear_model.html#logistic-regression
  n_iter_i = _check_optimize_result(
/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.
  _warn_prf(average, modifier, msg_start, len(result))
/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.
  _warn_prf(average, modifier, msg_start, len(result))
/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.
  _warn_prf(average, "true nor predicted", "F-score is", len(true_sum))
/home/pruthvish/JRF/RoadNetwork/RoadNetwork_VirtualEnv/lib/python3.8/site-packages/sklearn/linear_model/_logistic.py:444: ConvergenceWarning: lbfgs failed to converge (status=1):
STOP: TOTAL NO. of ITERATIONS REACHED LIMIT.

Increase the number of iterations (max_iter) or scale the data as shown in:
    https://scikit-learn.org/stable/modules/preprocessing.html
Please also refer to the documentation for alternative solver options:
    https://scikit-learn.org/stable/modules/linear_model.html#logistic-regression
  n_iter_i = _check_optimize_result(
/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.
  _warn_prf(average, modifier, msg_start, len(result))
/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.
  _warn_prf(average, modifier, msg_start, len(result))
/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.
  _warn_prf(average, "true nor predicted", "F-score is", len(true_sum))
/home/pruthvish/JRF/RoadNetwork/RoadNetwork_VirtualEnv/lib/python3.8/site-packages/sklearn/linear_model/_logistic.py:444: ConvergenceWarning: lbfgs failed to converge (status=1):
STOP: TOTAL NO. of ITERATIONS REACHED LIMIT.

Increase the number of iterations (max_iter) or scale the data as shown in:
    https://scikit-learn.org/stable/modules/preprocessing.html
Please also refer to the documentation for alternative solver options:
    https://scikit-learn.org/stable/modules/linear_model.html#logistic-regression
  n_iter_i = _check_optimize_result(
/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.
  _warn_prf(average, modifier, msg_start, len(result))
/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.
  _warn_prf(average, modifier, msg_start, len(result))
/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.
  _warn_prf(average, "true nor predicted", "F-score is", len(true_sum))
/home/pruthvish/JRF/RoadNetwork/RoadNetwork_VirtualEnv/lib/python3.8/site-packages/sklearn/linear_model/_logistic.py:444: ConvergenceWarning: lbfgs failed to converge (status=1):
STOP: TOTAL NO. of ITERATIONS REACHED LIMIT.

Increase the number of iterations (max_iter) or scale the data as shown in:
    https://scikit-learn.org/stable/modules/preprocessing.html
Please also refer to the documentation for alternative solver options:
    https://scikit-learn.org/stable/modules/linear_model.html#logistic-regression
  n_iter_i = _check_optimize_result(
/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.
  _warn_prf(average, modifier, msg_start, len(result))
/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.
  _warn_prf(average, modifier, msg_start, len(result))
/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.
  _warn_prf(average, "true nor predicted", "F-score is", len(true_sum))
/home/pruthvish/JRF/RoadNetwork/RoadNetwork_VirtualEnv/lib/python3.8/site-packages/sklearn/linear_model/_logistic.py:444: ConvergenceWarning: lbfgs failed to converge (status=1):
STOP: TOTAL NO. of ITERATIONS REACHED LIMIT.

Increase the number of iterations (max_iter) or scale the data as shown in:
    https://scikit-learn.org/stable/modules/preprocessing.html
Please also refer to the documentation for alternative solver options:
    https://scikit-learn.org/stable/modules/linear_model.html#logistic-regression
  n_iter_i = _check_optimize_result(
/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.
  _warn_prf(average, modifier, msg_start, len(result))
/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.
  _warn_prf(average, modifier, msg_start, len(result))
/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.
  _warn_prf(average, "true nor predicted", "F-score is", len(true_sum))
/home/pruthvish/JRF/RoadNetwork/RoadNetwork_VirtualEnv/lib/python3.8/site-packages/sklearn/linear_model/_logistic.py:444: ConvergenceWarning: lbfgs failed to converge (status=1):
STOP: TOTAL NO. of ITERATIONS REACHED LIMIT.

Increase the number of iterations (max_iter) or scale the data as shown in:
    https://scikit-learn.org/stable/modules/preprocessing.html
Please also refer to the documentation for alternative solver options:
    https://scikit-learn.org/stable/modules/linear_model.html#logistic-regression
  n_iter_i = _check_optimize_result(
/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.
  _warn_prf(average, modifier, msg_start, len(result))
/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.
  _warn_prf(average, modifier, msg_start, len(result))
/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.
  _warn_prf(average, "true nor predicted", "F-score is", len(true_sum))
/home/pruthvish/JRF/RoadNetwork/RoadNetwork_VirtualEnv/lib/python3.8/site-packages/sklearn/linear_model/_logistic.py:444: ConvergenceWarning: lbfgs failed to converge (status=1):
STOP: TOTAL NO. of ITERATIONS REACHED LIMIT.

Increase the number of iterations (max_iter) or scale the data as shown in:
    https://scikit-learn.org/stable/modules/preprocessing.html
Please also refer to the documentation for alternative solver options:
    https://scikit-learn.org/stable/modules/linear_model.html#logistic-regression
  n_iter_i = _check_optimize_result(
/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.
  _warn_prf(average, modifier, msg_start, len(result))
/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.
  _warn_prf(average, modifier, msg_start, len(result))
/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.
  _warn_prf(average, "true nor predicted", "F-score is", len(true_sum))
/home/pruthvish/JRF/RoadNetwork/RoadNetwork_VirtualEnv/lib/python3.8/site-packages/sklearn/linear_model/_logistic.py:444: ConvergenceWarning: lbfgs failed to converge (status=1):
STOP: TOTAL NO. of ITERATIONS REACHED LIMIT.

Increase the number of iterations (max_iter) or scale the data as shown in:
    https://scikit-learn.org/stable/modules/preprocessing.html
Please also refer to the documentation for alternative solver options:
    https://scikit-learn.org/stable/modules/linear_model.html#logistic-regression
  n_iter_i = _check_optimize_result(
/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.
  _warn_prf(average, modifier, msg_start, len(result))
/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.
  _warn_prf(average, modifier, msg_start, len(result))
/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.
  _warn_prf(average, "true nor predicted", "F-score is", len(true_sum))
/home/pruthvish/JRF/RoadNetwork/RoadNetwork_VirtualEnv/lib/python3.8/site-packages/sklearn/linear_model/_logistic.py:444: ConvergenceWarning: lbfgs failed to converge (status=1):
STOP: TOTAL NO. of ITERATIONS REACHED LIMIT.

Increase the number of iterations (max_iter) or scale the data as shown in:
    https://scikit-learn.org/stable/modules/preprocessing.html
Please also refer to the documentation for alternative solver options:
    https://scikit-learn.org/stable/modules/linear_model.html#logistic-regression
  n_iter_i = _check_optimize_result(
/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.
  _warn_prf(average, modifier, msg_start, len(result))
/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.
  _warn_prf(average, modifier, msg_start, len(result))
/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.
  _warn_prf(average, "true nor predicted", "F-score is", len(true_sum))

Feature set-2

/home/pruthvish/JRF/RoadNetwork/RoadNetwork_VirtualEnv/lib/python3.8/site-packages/sklearn/linear_model/_logistic.py:444: ConvergenceWarning: lbfgs failed to converge (status=1):
STOP: TOTAL NO. of ITERATIONS REACHED LIMIT.

Increase the number of iterations (max_iter) or scale the data as shown in:
    https://scikit-learn.org/stable/modules/preprocessing.html
Please also refer to the documentation for alternative solver options:
    https://scikit-learn.org/stable/modules/linear_model.html#logistic-regression
  n_iter_i = _check_optimize_result(
/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.
  _warn_prf(average, modifier, msg_start, len(result))
/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.
  _warn_prf(average, modifier, msg_start, len(result))
/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.
  _warn_prf(average, "true nor predicted", "F-score is", len(true_sum))
/home/pruthvish/JRF/RoadNetwork/RoadNetwork_VirtualEnv/lib/python3.8/site-packages/sklearn/linear_model/_logistic.py:444: ConvergenceWarning: lbfgs failed to converge (status=1):
STOP: TOTAL NO. of ITERATIONS REACHED LIMIT.

Increase the number of iterations (max_iter) or scale the data as shown in:
    https://scikit-learn.org/stable/modules/preprocessing.html
Please also refer to the documentation for alternative solver options:
    https://scikit-learn.org/stable/modules/linear_model.html#logistic-regression
  n_iter_i = _check_optimize_result(
/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.
  _warn_prf(average, modifier, msg_start, len(result))
/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.
  _warn_prf(average, modifier, msg_start, len(result))
/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.
  _warn_prf(average, "true nor predicted", "F-score is", len(true_sum))
/home/pruthvish/JRF/RoadNetwork/RoadNetwork_VirtualEnv/lib/python3.8/site-packages/sklearn/linear_model/_logistic.py:444: ConvergenceWarning: lbfgs failed to converge (status=1):
STOP: TOTAL NO. of ITERATIONS REACHED LIMIT.

Increase the number of iterations (max_iter) or scale the data as shown in:
    https://scikit-learn.org/stable/modules/preprocessing.html
Please also refer to the documentation for alternative solver options:
    https://scikit-learn.org/stable/modules/linear_model.html#logistic-regression
  n_iter_i = _check_optimize_result(
/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.
  _warn_prf(average, modifier, msg_start, len(result))
/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.
  _warn_prf(average, modifier, msg_start, len(result))
/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.
  _warn_prf(average, "true nor predicted", "F-score is", len(true_sum))
/home/pruthvish/JRF/RoadNetwork/RoadNetwork_VirtualEnv/lib/python3.8/site-packages/sklearn/linear_model/_logistic.py:444: ConvergenceWarning: lbfgs failed to converge (status=1):
STOP: TOTAL NO. of ITERATIONS REACHED LIMIT.

Increase the number of iterations (max_iter) or scale the data as shown in:
    https://scikit-learn.org/stable/modules/preprocessing.html
Please also refer to the documentation for alternative solver options:
    https://scikit-learn.org/stable/modules/linear_model.html#logistic-regression
  n_iter_i = _check_optimize_result(
/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.
  _warn_prf(average, modifier, msg_start, len(result))
/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.
  _warn_prf(average, modifier, msg_start, len(result))
/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.
  _warn_prf(average, "true nor predicted", "F-score is", len(true_sum))
/home/pruthvish/JRF/RoadNetwork/RoadNetwork_VirtualEnv/lib/python3.8/site-packages/sklearn/linear_model/_logistic.py:444: ConvergenceWarning: lbfgs failed to converge (status=1):
STOP: TOTAL NO. of ITERATIONS REACHED LIMIT.

Increase the number of iterations (max_iter) or scale the data as shown in:
    https://scikit-learn.org/stable/modules/preprocessing.html
Please also refer to the documentation for alternative solver options:
    https://scikit-learn.org/stable/modules/linear_model.html#logistic-regression
  n_iter_i = _check_optimize_result(
/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.
  _warn_prf(average, modifier, msg_start, len(result))
/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.
  _warn_prf(average, modifier, msg_start, len(result))
/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.
  _warn_prf(average, "true nor predicted", "F-score is", len(true_sum))
/home/pruthvish/JRF/RoadNetwork/RoadNetwork_VirtualEnv/lib/python3.8/site-packages/sklearn/linear_model/_logistic.py:444: ConvergenceWarning: lbfgs failed to converge (status=1):
STOP: TOTAL NO. of ITERATIONS REACHED LIMIT.

Increase the number of iterations (max_iter) or scale the data as shown in:
    https://scikit-learn.org/stable/modules/preprocessing.html
Please also refer to the documentation for alternative solver options:
    https://scikit-learn.org/stable/modules/linear_model.html#logistic-regression
  n_iter_i = _check_optimize_result(
/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.
  _warn_prf(average, modifier, msg_start, len(result))
/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.
  _warn_prf(average, modifier, msg_start, len(result))
/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.
  _warn_prf(average, "true nor predicted", "F-score is", len(true_sum))
/home/pruthvish/JRF/RoadNetwork/RoadNetwork_VirtualEnv/lib/python3.8/site-packages/sklearn/linear_model/_logistic.py:444: ConvergenceWarning: lbfgs failed to converge (status=1):
STOP: TOTAL NO. of ITERATIONS REACHED LIMIT.

Increase the number of iterations (max_iter) or scale the data as shown in:
    https://scikit-learn.org/stable/modules/preprocessing.html
Please also refer to the documentation for alternative solver options:
    https://scikit-learn.org/stable/modules/linear_model.html#logistic-regression
  n_iter_i = _check_optimize_result(
/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.
  _warn_prf(average, modifier, msg_start, len(result))
/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.
  _warn_prf(average, modifier, msg_start, len(result))
/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.
  _warn_prf(average, "true nor predicted", "F-score is", len(true_sum))
/home/pruthvish/JRF/RoadNetwork/RoadNetwork_VirtualEnv/lib/python3.8/site-packages/sklearn/linear_model/_logistic.py:444: ConvergenceWarning: lbfgs failed to converge (status=1):
STOP: TOTAL NO. of ITERATIONS REACHED LIMIT.

Increase the number of iterations (max_iter) or scale the data as shown in:
    https://scikit-learn.org/stable/modules/preprocessing.html
Please also refer to the documentation for alternative solver options:
    https://scikit-learn.org/stable/modules/linear_model.html#logistic-regression
  n_iter_i = _check_optimize_result(
/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.
  _warn_prf(average, modifier, msg_start, len(result))
/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.
  _warn_prf(average, modifier, msg_start, len(result))
/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.
  _warn_prf(average, "true nor predicted", "F-score is", len(true_sum))
/home/pruthvish/JRF/RoadNetwork/RoadNetwork_VirtualEnv/lib/python3.8/site-packages/sklearn/linear_model/_logistic.py:444: ConvergenceWarning: lbfgs failed to converge (status=1):
STOP: TOTAL NO. of ITERATIONS REACHED LIMIT.

Increase the number of iterations (max_iter) or scale the data as shown in:
    https://scikit-learn.org/stable/modules/preprocessing.html
Please also refer to the documentation for alternative solver options:
    https://scikit-learn.org/stable/modules/linear_model.html#logistic-regression
  n_iter_i = _check_optimize_result(
/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.
  _warn_prf(average, modifier, msg_start, len(result))
/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.
  _warn_prf(average, modifier, msg_start, len(result))
/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.
  _warn_prf(average, "true nor predicted", "F-score is", len(true_sum))
/home/pruthvish/JRF/RoadNetwork/RoadNetwork_VirtualEnv/lib/python3.8/site-packages/sklearn/linear_model/_logistic.py:444: ConvergenceWarning: lbfgs failed to converge (status=1):
STOP: TOTAL NO. of ITERATIONS REACHED LIMIT.

Increase the number of iterations (max_iter) or scale the data as shown in:
    https://scikit-learn.org/stable/modules/preprocessing.html
Please also refer to the documentation for alternative solver options:
    https://scikit-learn.org/stable/modules/linear_model.html#logistic-regression
  n_iter_i = _check_optimize_result(
/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.
  _warn_prf(average, modifier, msg_start, len(result))
/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.
  _warn_prf(average, modifier, msg_start, len(result))
/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.
  _warn_prf(average, "true nor predicted", "F-score is", len(true_sum))

Feature set-3

/home/pruthvish/JRF/RoadNetwork/RoadNetwork_VirtualEnv/lib/python3.8/site-packages/sklearn/linear_model/_logistic.py:444: ConvergenceWarning: lbfgs failed to converge (status=1):
STOP: TOTAL NO. of ITERATIONS REACHED LIMIT.

Increase the number of iterations (max_iter) or scale the data as shown in:
    https://scikit-learn.org/stable/modules/preprocessing.html
Please also refer to the documentation for alternative solver options:
    https://scikit-learn.org/stable/modules/linear_model.html#logistic-regression
  n_iter_i = _check_optimize_result(
/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.
  _warn_prf(average, modifier, msg_start, len(result))
/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.
  _warn_prf(average, modifier, msg_start, len(result))
/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.
  _warn_prf(average, "true nor predicted", "F-score is", len(true_sum))
/home/pruthvish/JRF/RoadNetwork/RoadNetwork_VirtualEnv/lib/python3.8/site-packages/sklearn/linear_model/_logistic.py:444: ConvergenceWarning: lbfgs failed to converge (status=1):
STOP: TOTAL NO. of ITERATIONS REACHED LIMIT.

Increase the number of iterations (max_iter) or scale the data as shown in:
    https://scikit-learn.org/stable/modules/preprocessing.html
Please also refer to the documentation for alternative solver options:
    https://scikit-learn.org/stable/modules/linear_model.html#logistic-regression
  n_iter_i = _check_optimize_result(
/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.
  _warn_prf(average, modifier, msg_start, len(result))
/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.
  _warn_prf(average, modifier, msg_start, len(result))
/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.
  _warn_prf(average, "true nor predicted", "F-score is", len(true_sum))
/home/pruthvish/JRF/RoadNetwork/RoadNetwork_VirtualEnv/lib/python3.8/site-packages/sklearn/linear_model/_logistic.py:444: ConvergenceWarning: lbfgs failed to converge (status=1):
STOP: TOTAL NO. of ITERATIONS REACHED LIMIT.

Increase the number of iterations (max_iter) or scale the data as shown in:
    https://scikit-learn.org/stable/modules/preprocessing.html
Please also refer to the documentation for alternative solver options:
    https://scikit-learn.org/stable/modules/linear_model.html#logistic-regression
  n_iter_i = _check_optimize_result(
/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.
  _warn_prf(average, modifier, msg_start, len(result))
/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.
  _warn_prf(average, modifier, msg_start, len(result))
/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.
  _warn_prf(average, "true nor predicted", "F-score is", len(true_sum))
/home/pruthvish/JRF/RoadNetwork/RoadNetwork_VirtualEnv/lib/python3.8/site-packages/sklearn/linear_model/_logistic.py:444: ConvergenceWarning: lbfgs failed to converge (status=1):
STOP: TOTAL NO. of ITERATIONS REACHED LIMIT.

Increase the number of iterations (max_iter) or scale the data as shown in:
    https://scikit-learn.org/stable/modules/preprocessing.html
Please also refer to the documentation for alternative solver options:
    https://scikit-learn.org/stable/modules/linear_model.html#logistic-regression
  n_iter_i = _check_optimize_result(
/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.
  _warn_prf(average, modifier, msg_start, len(result))
/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.
  _warn_prf(average, modifier, msg_start, len(result))
/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.
  _warn_prf(average, "true nor predicted", "F-score is", len(true_sum))
/home/pruthvish/JRF/RoadNetwork/RoadNetwork_VirtualEnv/lib/python3.8/site-packages/sklearn/linear_model/_logistic.py:444: ConvergenceWarning: lbfgs failed to converge (status=1):
STOP: TOTAL NO. of ITERATIONS REACHED LIMIT.

Increase the number of iterations (max_iter) or scale the data as shown in:
    https://scikit-learn.org/stable/modules/preprocessing.html
Please also refer to the documentation for alternative solver options:
    https://scikit-learn.org/stable/modules/linear_model.html#logistic-regression
  n_iter_i = _check_optimize_result(
/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.
  _warn_prf(average, modifier, msg_start, len(result))
/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.
  _warn_prf(average, modifier, msg_start, len(result))
/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.
  _warn_prf(average, "true nor predicted", "F-score is", len(true_sum))
/home/pruthvish/JRF/RoadNetwork/RoadNetwork_VirtualEnv/lib/python3.8/site-packages/sklearn/linear_model/_logistic.py:444: ConvergenceWarning: lbfgs failed to converge (status=1):
STOP: TOTAL NO. of ITERATIONS REACHED LIMIT.

Increase the number of iterations (max_iter) or scale the data as shown in:
    https://scikit-learn.org/stable/modules/preprocessing.html
Please also refer to the documentation for alternative solver options:
    https://scikit-learn.org/stable/modules/linear_model.html#logistic-regression
  n_iter_i = _check_optimize_result(
/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.
  _warn_prf(average, modifier, msg_start, len(result))
/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.
  _warn_prf(average, modifier, msg_start, len(result))
/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.
  _warn_prf(average, "true nor predicted", "F-score is", len(true_sum))
/home/pruthvish/JRF/RoadNetwork/RoadNetwork_VirtualEnv/lib/python3.8/site-packages/sklearn/linear_model/_logistic.py:444: ConvergenceWarning: lbfgs failed to converge (status=1):
STOP: TOTAL NO. of ITERATIONS REACHED LIMIT.

Increase the number of iterations (max_iter) or scale the data as shown in:
    https://scikit-learn.org/stable/modules/preprocessing.html
Please also refer to the documentation for alternative solver options:
    https://scikit-learn.org/stable/modules/linear_model.html#logistic-regression
  n_iter_i = _check_optimize_result(
/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.
  _warn_prf(average, modifier, msg_start, len(result))
/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.
  _warn_prf(average, modifier, msg_start, len(result))
/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.
  _warn_prf(average, "true nor predicted", "F-score is", len(true_sum))
/home/pruthvish/JRF/RoadNetwork/RoadNetwork_VirtualEnv/lib/python3.8/site-packages/sklearn/linear_model/_logistic.py:444: ConvergenceWarning: lbfgs failed to converge (status=1):
STOP: TOTAL NO. of ITERATIONS REACHED LIMIT.

Increase the number of iterations (max_iter) or scale the data as shown in:
    https://scikit-learn.org/stable/modules/preprocessing.html
Please also refer to the documentation for alternative solver options:
    https://scikit-learn.org/stable/modules/linear_model.html#logistic-regression
  n_iter_i = _check_optimize_result(
/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.
  _warn_prf(average, modifier, msg_start, len(result))
/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.
  _warn_prf(average, modifier, msg_start, len(result))
/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.
  _warn_prf(average, "true nor predicted", "F-score is", len(true_sum))
/home/pruthvish/JRF/RoadNetwork/RoadNetwork_VirtualEnv/lib/python3.8/site-packages/sklearn/linear_model/_logistic.py:444: ConvergenceWarning: lbfgs failed to converge (status=1):
STOP: TOTAL NO. of ITERATIONS REACHED LIMIT.

Increase the number of iterations (max_iter) or scale the data as shown in:
    https://scikit-learn.org/stable/modules/preprocessing.html
Please also refer to the documentation for alternative solver options:
    https://scikit-learn.org/stable/modules/linear_model.html#logistic-regression
  n_iter_i = _check_optimize_result(
/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.
  _warn_prf(average, modifier, msg_start, len(result))
/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.
  _warn_prf(average, modifier, msg_start, len(result))
/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.
  _warn_prf(average, "true nor predicted", "F-score is", len(true_sum))
/home/pruthvish/JRF/RoadNetwork/RoadNetwork_VirtualEnv/lib/python3.8/site-packages/sklearn/linear_model/_logistic.py:444: ConvergenceWarning: lbfgs failed to converge (status=1):
STOP: TOTAL NO. of ITERATIONS REACHED LIMIT.

Increase the number of iterations (max_iter) or scale the data as shown in:
    https://scikit-learn.org/stable/modules/preprocessing.html
Please also refer to the documentation for alternative solver options:
    https://scikit-learn.org/stable/modules/linear_model.html#logistic-regression
  n_iter_i = _check_optimize_result(
/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.
  _warn_prf(average, modifier, msg_start, len(result))
/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.
  _warn_prf(average, modifier, msg_start, len(result))
/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.
  _warn_prf(average, "true nor predicted", "F-score is", len(true_sum))

Feature set-4

/home/pruthvish/JRF/RoadNetwork/RoadNetwork_VirtualEnv/lib/python3.8/site-packages/sklearn/linear_model/_logistic.py:444: ConvergenceWarning: lbfgs failed to converge (status=1):
STOP: TOTAL NO. of ITERATIONS REACHED LIMIT.

Increase the number of iterations (max_iter) or scale the data as shown in:
    https://scikit-learn.org/stable/modules/preprocessing.html
Please also refer to the documentation for alternative solver options:
    https://scikit-learn.org/stable/modules/linear_model.html#logistic-regression
  n_iter_i = _check_optimize_result(
/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.
  _warn_prf(average, modifier, msg_start, len(result))
/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.
  _warn_prf(average, modifier, msg_start, len(result))
/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.
  _warn_prf(average, "true nor predicted", "F-score is", len(true_sum))
/home/pruthvish/JRF/RoadNetwork/RoadNetwork_VirtualEnv/lib/python3.8/site-packages/sklearn/linear_model/_logistic.py:444: ConvergenceWarning: lbfgs failed to converge (status=1):
STOP: TOTAL NO. of ITERATIONS REACHED LIMIT.

Increase the number of iterations (max_iter) or scale the data as shown in:
    https://scikit-learn.org/stable/modules/preprocessing.html
Please also refer to the documentation for alternative solver options:
    https://scikit-learn.org/stable/modules/linear_model.html#logistic-regression
  n_iter_i = _check_optimize_result(
/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.
  _warn_prf(average, modifier, msg_start, len(result))
/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.
  _warn_prf(average, modifier, msg_start, len(result))
/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.
  _warn_prf(average, "true nor predicted", "F-score is", len(true_sum))
/home/pruthvish/JRF/RoadNetwork/RoadNetwork_VirtualEnv/lib/python3.8/site-packages/sklearn/linear_model/_logistic.py:444: ConvergenceWarning: lbfgs failed to converge (status=1):
STOP: TOTAL NO. of ITERATIONS REACHED LIMIT.

Increase the number of iterations (max_iter) or scale the data as shown in:
    https://scikit-learn.org/stable/modules/preprocessing.html
Please also refer to the documentation for alternative solver options:
    https://scikit-learn.org/stable/modules/linear_model.html#logistic-regression
  n_iter_i = _check_optimize_result(
/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.
  _warn_prf(average, modifier, msg_start, len(result))
/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.
  _warn_prf(average, modifier, msg_start, len(result))
/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.
  _warn_prf(average, "true nor predicted", "F-score is", len(true_sum))
/home/pruthvish/JRF/RoadNetwork/RoadNetwork_VirtualEnv/lib/python3.8/site-packages/sklearn/linear_model/_logistic.py:444: ConvergenceWarning: lbfgs failed to converge (status=1):
STOP: TOTAL NO. of ITERATIONS REACHED LIMIT.

Increase the number of iterations (max_iter) or scale the data as shown in:
    https://scikit-learn.org/stable/modules/preprocessing.html
Please also refer to the documentation for alternative solver options:
    https://scikit-learn.org/stable/modules/linear_model.html#logistic-regression
  n_iter_i = _check_optimize_result(
/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.
  _warn_prf(average, modifier, msg_start, len(result))
/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.
  _warn_prf(average, modifier, msg_start, len(result))
/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.
  _warn_prf(average, "true nor predicted", "F-score is", len(true_sum))
/home/pruthvish/JRF/RoadNetwork/RoadNetwork_VirtualEnv/lib/python3.8/site-packages/sklearn/linear_model/_logistic.py:444: ConvergenceWarning: lbfgs failed to converge (status=1):
STOP: TOTAL NO. of ITERATIONS REACHED LIMIT.

Increase the number of iterations (max_iter) or scale the data as shown in:
    https://scikit-learn.org/stable/modules/preprocessing.html
Please also refer to the documentation for alternative solver options:
    https://scikit-learn.org/stable/modules/linear_model.html#logistic-regression
  n_iter_i = _check_optimize_result(
/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.
  _warn_prf(average, modifier, msg_start, len(result))
/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.
  _warn_prf(average, modifier, msg_start, len(result))
/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.
  _warn_prf(average, "true nor predicted", "F-score is", len(true_sum))
/home/pruthvish/JRF/RoadNetwork/RoadNetwork_VirtualEnv/lib/python3.8/site-packages/sklearn/linear_model/_logistic.py:444: ConvergenceWarning: lbfgs failed to converge (status=1):
STOP: TOTAL NO. of ITERATIONS REACHED LIMIT.

Increase the number of iterations (max_iter) or scale the data as shown in:
    https://scikit-learn.org/stable/modules/preprocessing.html
Please also refer to the documentation for alternative solver options:
    https://scikit-learn.org/stable/modules/linear_model.html#logistic-regression
  n_iter_i = _check_optimize_result(
/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.
  _warn_prf(average, modifier, msg_start, len(result))
/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.
  _warn_prf(average, modifier, msg_start, len(result))
/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.
  _warn_prf(average, "true nor predicted", "F-score is", len(true_sum))
/home/pruthvish/JRF/RoadNetwork/RoadNetwork_VirtualEnv/lib/python3.8/site-packages/sklearn/linear_model/_logistic.py:444: ConvergenceWarning: lbfgs failed to converge (status=1):
STOP: TOTAL NO. of ITERATIONS REACHED LIMIT.

Increase the number of iterations (max_iter) or scale the data as shown in:
    https://scikit-learn.org/stable/modules/preprocessing.html
Please also refer to the documentation for alternative solver options:
    https://scikit-learn.org/stable/modules/linear_model.html#logistic-regression
  n_iter_i = _check_optimize_result(
/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.
  _warn_prf(average, modifier, msg_start, len(result))
/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.
  _warn_prf(average, modifier, msg_start, len(result))
/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.
  _warn_prf(average, "true nor predicted", "F-score is", len(true_sum))
/home/pruthvish/JRF/RoadNetwork/RoadNetwork_VirtualEnv/lib/python3.8/site-packages/sklearn/linear_model/_logistic.py:444: ConvergenceWarning: lbfgs failed to converge (status=1):
STOP: TOTAL NO. of ITERATIONS REACHED LIMIT.

Increase the number of iterations (max_iter) or scale the data as shown in:
    https://scikit-learn.org/stable/modules/preprocessing.html
Please also refer to the documentation for alternative solver options:
    https://scikit-learn.org/stable/modules/linear_model.html#logistic-regression
  n_iter_i = _check_optimize_result(
/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.
  _warn_prf(average, modifier, msg_start, len(result))
/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.
  _warn_prf(average, modifier, msg_start, len(result))
/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.
  _warn_prf(average, "true nor predicted", "F-score is", len(true_sum))
/home/pruthvish/JRF/RoadNetwork/RoadNetwork_VirtualEnv/lib/python3.8/site-packages/sklearn/linear_model/_logistic.py:444: ConvergenceWarning: lbfgs failed to converge (status=1):
STOP: TOTAL NO. of ITERATIONS REACHED LIMIT.

Increase the number of iterations (max_iter) or scale the data as shown in:
    https://scikit-learn.org/stable/modules/preprocessing.html
Please also refer to the documentation for alternative solver options:
    https://scikit-learn.org/stable/modules/linear_model.html#logistic-regression
  n_iter_i = _check_optimize_result(
/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.
  _warn_prf(average, modifier, msg_start, len(result))
/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.
  _warn_prf(average, modifier, msg_start, len(result))
/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.
  _warn_prf(average, "true nor predicted", "F-score is", len(true_sum))
/home/pruthvish/JRF/RoadNetwork/RoadNetwork_VirtualEnv/lib/python3.8/site-packages/sklearn/linear_model/_logistic.py:444: ConvergenceWarning: lbfgs failed to converge (status=1):
STOP: TOTAL NO. of ITERATIONS REACHED LIMIT.

Increase the number of iterations (max_iter) or scale the data as shown in:
    https://scikit-learn.org/stable/modules/preprocessing.html
Please also refer to the documentation for alternative solver options:
    https://scikit-learn.org/stable/modules/linear_model.html#logistic-regression
  n_iter_i = _check_optimize_result(
/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.
  _warn_prf(average, modifier, msg_start, len(result))
/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.
  _warn_prf(average, modifier, msg_start, len(result))
/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.
  _warn_prf(average, "true nor predicted", "F-score is", len(true_sum))

Classifier, ClassifierName RandomForestClassifier(max_depth=20) RF
Feature set-1

/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.
  _warn_prf(average, modifier, msg_start, len(result))
/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.
  _warn_prf(average, modifier, msg_start, len(result))
/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.
  _warn_prf(average, "true nor predicted", "F-score is", len(true_sum))
/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.
  _warn_prf(average, modifier, msg_start, len(result))
/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.
  _warn_prf(average, modifier, msg_start, len(result))
/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.
  _warn_prf(average, "true nor predicted", "F-score is", len(true_sum))
/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.
  _warn_prf(average, modifier, msg_start, len(result))
/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.
  _warn_prf(average, modifier, msg_start, len(result))
/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.
  _warn_prf(average, "true nor predicted", "F-score is", len(true_sum))
/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.
  _warn_prf(average, modifier, msg_start, len(result))
/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.
  _warn_prf(average, modifier, msg_start, len(result))
/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.
  _warn_prf(average, "true nor predicted", "F-score is", len(true_sum))
/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.
  _warn_prf(average, modifier, msg_start, len(result))
/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.
  _warn_prf(average, modifier, msg_start, len(result))
/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.
  _warn_prf(average, "true nor predicted", "F-score is", len(true_sum))
/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.
  _warn_prf(average, modifier, msg_start, len(result))
/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.
  _warn_prf(average, modifier, msg_start, len(result))
/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.
  _warn_prf(average, "true nor predicted", "F-score is", len(true_sum))
/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.
  _warn_prf(average, modifier, msg_start, len(result))
/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.
  _warn_prf(average, modifier, msg_start, len(result))
/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.
  _warn_prf(average, "true nor predicted", "F-score is", len(true_sum))
/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.
  _warn_prf(average, modifier, msg_start, len(result))
/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.
  _warn_prf(average, modifier, msg_start, len(result))
/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.
  _warn_prf(average, "true nor predicted", "F-score is", len(true_sum))
/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.
  _warn_prf(average, modifier, msg_start, len(result))
/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.
  _warn_prf(average, modifier, msg_start, len(result))
/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.
  _warn_prf(average, "true nor predicted", "F-score is", len(true_sum))
/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.
  _warn_prf(average, modifier, msg_start, len(result))
/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.
  _warn_prf(average, modifier, msg_start, len(result))
/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.
  _warn_prf(average, "true nor predicted", "F-score is", len(true_sum))

Feature set-2

/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.
  _warn_prf(average, modifier, msg_start, len(result))
/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.
  _warn_prf(average, modifier, msg_start, len(result))
/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.
  _warn_prf(average, "true nor predicted", "F-score is", len(true_sum))
/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.
  _warn_prf(average, modifier, msg_start, len(result))
/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.
  _warn_prf(average, modifier, msg_start, len(result))
/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.
  _warn_prf(average, "true nor predicted", "F-score is", len(true_sum))
/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.
  _warn_prf(average, modifier, msg_start, len(result))
/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.
  _warn_prf(average, modifier, msg_start, len(result))
/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.
  _warn_prf(average, "true nor predicted", "F-score is", len(true_sum))
/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.
  _warn_prf(average, modifier, msg_start, len(result))
/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.
  _warn_prf(average, modifier, msg_start, len(result))
/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.
  _warn_prf(average, "true nor predicted", "F-score is", len(true_sum))
/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.
  _warn_prf(average, modifier, msg_start, len(result))
/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.
  _warn_prf(average, modifier, msg_start, len(result))
/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.
  _warn_prf(average, "true nor predicted", "F-score is", len(true_sum))
/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.
  _warn_prf(average, modifier, msg_start, len(result))
/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.
  _warn_prf(average, modifier, msg_start, len(result))
/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.
  _warn_prf(average, "true nor predicted", "F-score is", len(true_sum))
/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.
  _warn_prf(average, modifier, msg_start, len(result))
/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.
  _warn_prf(average, modifier, msg_start, len(result))
/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.
  _warn_prf(average, "true nor predicted", "F-score is", len(true_sum))
/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.
  _warn_prf(average, modifier, msg_start, len(result))
/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.
  _warn_prf(average, modifier, msg_start, len(result))
/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.
  _warn_prf(average, "true nor predicted", "F-score is", len(true_sum))
/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.
  _warn_prf(average, modifier, msg_start, len(result))
/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.
  _warn_prf(average, modifier, msg_start, len(result))
/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.
  _warn_prf(average, "true nor predicted", "F-score is", len(true_sum))
/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.
  _warn_prf(average, modifier, msg_start, len(result))
/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.
  _warn_prf(average, modifier, msg_start, len(result))
/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.
  _warn_prf(average, "true nor predicted", "F-score is", len(true_sum))

Feature set-3

/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.
  _warn_prf(average, modifier, msg_start, len(result))
/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.
  _warn_prf(average, modifier, msg_start, len(result))
/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.
  _warn_prf(average, "true nor predicted", "F-score is", len(true_sum))
/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.
  _warn_prf(average, modifier, msg_start, len(result))
/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.
  _warn_prf(average, modifier, msg_start, len(result))
/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.
  _warn_prf(average, "true nor predicted", "F-score is", len(true_sum))
/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.
  _warn_prf(average, modifier, msg_start, len(result))
/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.
  _warn_prf(average, modifier, msg_start, len(result))
/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.
  _warn_prf(average, "true nor predicted", "F-score is", len(true_sum))
/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.
  _warn_prf(average, modifier, msg_start, len(result))
/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.
  _warn_prf(average, modifier, msg_start, len(result))
/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.
  _warn_prf(average, "true nor predicted", "F-score is", len(true_sum))
/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.
  _warn_prf(average, modifier, msg_start, len(result))
/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.
  _warn_prf(average, modifier, msg_start, len(result))
/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.
  _warn_prf(average, "true nor predicted", "F-score is", len(true_sum))
/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.
  _warn_prf(average, modifier, msg_start, len(result))
/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.
  _warn_prf(average, modifier, msg_start, len(result))
/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.
  _warn_prf(average, "true nor predicted", "F-score is", len(true_sum))
/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.
  _warn_prf(average, modifier, msg_start, len(result))
/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.
  _warn_prf(average, modifier, msg_start, len(result))
/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.
  _warn_prf(average, "true nor predicted", "F-score is", len(true_sum))
/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.
  _warn_prf(average, modifier, msg_start, len(result))
/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.
  _warn_prf(average, modifier, msg_start, len(result))
/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.
  _warn_prf(average, "true nor predicted", "F-score is", len(true_sum))
/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.
  _warn_prf(average, modifier, msg_start, len(result))
/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.
  _warn_prf(average, modifier, msg_start, len(result))
/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.
  _warn_prf(average, "true nor predicted", "F-score is", len(true_sum))
/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.
  _warn_prf(average, modifier, msg_start, len(result))
/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.
  _warn_prf(average, modifier, msg_start, len(result))
/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.
  _warn_prf(average, "true nor predicted", "F-score is", len(true_sum))

Feature set-4

/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.
  _warn_prf(average, modifier, msg_start, len(result))
/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.
  _warn_prf(average, modifier, msg_start, len(result))
/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.
  _warn_prf(average, "true nor predicted", "F-score is", len(true_sum))
/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.
  _warn_prf(average, modifier, msg_start, len(result))
/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.
  _warn_prf(average, modifier, msg_start, len(result))
/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.
  _warn_prf(average, "true nor predicted", "F-score is", len(true_sum))
/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.
  _warn_prf(average, modifier, msg_start, len(result))
/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.
  _warn_prf(average, modifier, msg_start, len(result))
/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.
  _warn_prf(average, "true nor predicted", "F-score is", len(true_sum))
/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.
  _warn_prf(average, modifier, msg_start, len(result))
/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.
  _warn_prf(average, modifier, msg_start, len(result))
/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.
  _warn_prf(average, "true nor predicted", "F-score is", len(true_sum))
/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.
  _warn_prf(average, modifier, msg_start, len(result))
/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.
  _warn_prf(average, modifier, msg_start, len(result))
/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.
  _warn_prf(average, "true nor predicted", "F-score is", len(true_sum))
/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.
  _warn_prf(average, modifier, msg_start, len(result))
/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.
  _warn_prf(average, modifier, msg_start, len(result))
/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.
  _warn_prf(average, "true nor predicted", "F-score is", len(true_sum))
/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.
  _warn_prf(average, modifier, msg_start, len(result))
/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.
  _warn_prf(average, modifier, msg_start, len(result))
/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.
  _warn_prf(average, "true nor predicted", "F-score is", len(true_sum))
/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.
  _warn_prf(average, modifier, msg_start, len(result))
/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.
  _warn_prf(average, modifier, msg_start, len(result))
/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.
  _warn_prf(average, "true nor predicted", "F-score is", len(true_sum))
/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.
  _warn_prf(average, modifier, msg_start, len(result))
/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.
  _warn_prf(average, modifier, msg_start, len(result))
/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.
  _warn_prf(average, "true nor predicted", "F-score is", len(true_sum))
/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.
  _warn_prf(average, modifier, msg_start, len(result))
/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.
  _warn_prf(average, modifier, msg_start, len(result))
/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.
  _warn_prf(average, "true nor predicted", "F-score is", len(true_sum))

Classifier, ClassifierName DecisionTreeClassifier() DT
Feature set-1

/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.
  _warn_prf(average, modifier, msg_start, len(result))
/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.
  _warn_prf(average, modifier, msg_start, len(result))
/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.
  _warn_prf(average, "true nor predicted", "F-score is", len(true_sum))
/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.
  _warn_prf(average, modifier, msg_start, len(result))
/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.
  _warn_prf(average, modifier, msg_start, len(result))
/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.
  _warn_prf(average, "true nor predicted", "F-score is", len(true_sum))
/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.
  _warn_prf(average, modifier, msg_start, len(result))
/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.
  _warn_prf(average, modifier, msg_start, len(result))
/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.
  _warn_prf(average, "true nor predicted", "F-score is", len(true_sum))
/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.
  _warn_prf(average, modifier, msg_start, len(result))
/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.
  _warn_prf(average, modifier, msg_start, len(result))
/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.
  _warn_prf(average, "true nor predicted", "F-score is", len(true_sum))
/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.
  _warn_prf(average, modifier, msg_start, len(result))
/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.
  _warn_prf(average, modifier, msg_start, len(result))
/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.
  _warn_prf(average, "true nor predicted", "F-score is", len(true_sum))
/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.
  _warn_prf(average, modifier, msg_start, len(result))
/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.
  _warn_prf(average, modifier, msg_start, len(result))
/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.
  _warn_prf(average, "true nor predicted", "F-score is", len(true_sum))
/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.
  _warn_prf(average, modifier, msg_start, len(result))
/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.
  _warn_prf(average, modifier, msg_start, len(result))
/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.
  _warn_prf(average, "true nor predicted", "F-score is", len(true_sum))
/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.
  _warn_prf(average, modifier, msg_start, len(result))
/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.
  _warn_prf(average, modifier, msg_start, len(result))
/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.
  _warn_prf(average, "true nor predicted", "F-score is", len(true_sum))
/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.
  _warn_prf(average, modifier, msg_start, len(result))
/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.
  _warn_prf(average, modifier, msg_start, len(result))
/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.
  _warn_prf(average, "true nor predicted", "F-score is", len(true_sum))
/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.
  _warn_prf(average, modifier, msg_start, len(result))
/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.
  _warn_prf(average, modifier, msg_start, len(result))
/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.
  _warn_prf(average, "true nor predicted", "F-score is", len(true_sum))

Feature set-2

/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.
  _warn_prf(average, modifier, msg_start, len(result))
/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.
  _warn_prf(average, modifier, msg_start, len(result))
/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.
  _warn_prf(average, "true nor predicted", "F-score is", len(true_sum))
/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.
  _warn_prf(average, modifier, msg_start, len(result))
/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.
  _warn_prf(average, modifier, msg_start, len(result))
/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.
  _warn_prf(average, "true nor predicted", "F-score is", len(true_sum))
/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.
  _warn_prf(average, modifier, msg_start, len(result))
/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.
  _warn_prf(average, modifier, msg_start, len(result))
/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.
  _warn_prf(average, "true nor predicted", "F-score is", len(true_sum))
/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.
  _warn_prf(average, modifier, msg_start, len(result))
/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.
  _warn_prf(average, modifier, msg_start, len(result))
/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.
  _warn_prf(average, "true nor predicted", "F-score is", len(true_sum))
/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.
  _warn_prf(average, modifier, msg_start, len(result))
/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.
  _warn_prf(average, modifier, msg_start, len(result))
/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.
  _warn_prf(average, "true nor predicted", "F-score is", len(true_sum))
/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.
  _warn_prf(average, modifier, msg_start, len(result))
/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.
  _warn_prf(average, modifier, msg_start, len(result))
/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.
  _warn_prf(average, "true nor predicted", "F-score is", len(true_sum))
/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.
  _warn_prf(average, modifier, msg_start, len(result))
/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.
  _warn_prf(average, modifier, msg_start, len(result))
/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.
  _warn_prf(average, "true nor predicted", "F-score is", len(true_sum))
/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.
  _warn_prf(average, modifier, msg_start, len(result))
/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.
  _warn_prf(average, modifier, msg_start, len(result))
/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.
  _warn_prf(average, "true nor predicted", "F-score is", len(true_sum))
/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.
  _warn_prf(average, modifier, msg_start, len(result))
/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.
  _warn_prf(average, modifier, msg_start, len(result))
/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.
  _warn_prf(average, "true nor predicted", "F-score is", len(true_sum))
/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.
  _warn_prf(average, modifier, msg_start, len(result))
/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.
  _warn_prf(average, modifier, msg_start, len(result))
/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.
  _warn_prf(average, "true nor predicted", "F-score is", len(true_sum))
/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.
  _warn_prf(average, modifier, msg_start, len(result))
/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.
  _warn_prf(average, modifier, msg_start, len(result))
/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.
  _warn_prf(average, "true nor predicted", "F-score is", len(true_sum))

Feature set-3

/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.
  _warn_prf(average, modifier, msg_start, len(result))
/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.
  _warn_prf(average, modifier, msg_start, len(result))
/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.
  _warn_prf(average, "true nor predicted", "F-score is", len(true_sum))
/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.
  _warn_prf(average, modifier, msg_start, len(result))
/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.
  _warn_prf(average, modifier, msg_start, len(result))
/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.
  _warn_prf(average, "true nor predicted", "F-score is", len(true_sum))
/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.
  _warn_prf(average, modifier, msg_start, len(result))
/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.
  _warn_prf(average, modifier, msg_start, len(result))
/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.
  _warn_prf(average, "true nor predicted", "F-score is", len(true_sum))
/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.
  _warn_prf(average, modifier, msg_start, len(result))
/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.
  _warn_prf(average, modifier, msg_start, len(result))
/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.
  _warn_prf(average, "true nor predicted", "F-score is", len(true_sum))
/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.
  _warn_prf(average, modifier, msg_start, len(result))
/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.
  _warn_prf(average, modifier, msg_start, len(result))
/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.
  _warn_prf(average, "true nor predicted", "F-score is", len(true_sum))
/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.
  _warn_prf(average, modifier, msg_start, len(result))
/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.
  _warn_prf(average, modifier, msg_start, len(result))
/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.
  _warn_prf(average, "true nor predicted", "F-score is", len(true_sum))
/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.
  _warn_prf(average, modifier, msg_start, len(result))
/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.
  _warn_prf(average, modifier, msg_start, len(result))
/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.
  _warn_prf(average, "true nor predicted", "F-score is", len(true_sum))
/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.
  _warn_prf(average, modifier, msg_start, len(result))
/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.
  _warn_prf(average, modifier, msg_start, len(result))
/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.
  _warn_prf(average, "true nor predicted", "F-score is", len(true_sum))
/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.
  _warn_prf(average, modifier, msg_start, len(result))
/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.
  _warn_prf(average, modifier, msg_start, len(result))
/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.
  _warn_prf(average, "true nor predicted", "F-score is", len(true_sum))
/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.
  _warn_prf(average, modifier, msg_start, len(result))
/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.
  _warn_prf(average, modifier, msg_start, len(result))
/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.
  _warn_prf(average, "true nor predicted", "F-score is", len(true_sum))
/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.
  _warn_prf(average, modifier, msg_start, len(result))
/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.
  _warn_prf(average, modifier, msg_start, len(result))
/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.
  _warn_prf(average, "true nor predicted", "F-score is", len(true_sum))

Feature set-4

/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.
  _warn_prf(average, modifier, msg_start, len(result))
/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.
  _warn_prf(average, modifier, msg_start, len(result))
/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.
  _warn_prf(average, "true nor predicted", "F-score is", len(true_sum))
/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.
  _warn_prf(average, modifier, msg_start, len(result))
/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.
  _warn_prf(average, modifier, msg_start, len(result))
/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.
  _warn_prf(average, "true nor predicted", "F-score is", len(true_sum))
/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.
  _warn_prf(average, modifier, msg_start, len(result))
/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.
  _warn_prf(average, modifier, msg_start, len(result))
/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.
  _warn_prf(average, "true nor predicted", "F-score is", len(true_sum))
/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.
  _warn_prf(average, modifier, msg_start, len(result))
/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.
  _warn_prf(average, modifier, msg_start, len(result))
/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.
  _warn_prf(average, "true nor predicted", "F-score is", len(true_sum))
/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.
  _warn_prf(average, modifier, msg_start, len(result))
/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.
  _warn_prf(average, modifier, msg_start, len(result))
/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.
  _warn_prf(average, "true nor predicted", "F-score is", len(true_sum))
/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.
  _warn_prf(average, modifier, msg_start, len(result))
/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.
  _warn_prf(average, modifier, msg_start, len(result))
/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.
  _warn_prf(average, "true nor predicted", "F-score is", len(true_sum))
/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.
  _warn_prf(average, modifier, msg_start, len(result))
/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.
  _warn_prf(average, modifier, msg_start, len(result))
/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.
  _warn_prf(average, "true nor predicted", "F-score is", len(true_sum))
/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.
  _warn_prf(average, modifier, msg_start, len(result))
/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.
  _warn_prf(average, modifier, msg_start, len(result))
/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.
  _warn_prf(average, "true nor predicted", "F-score is", len(true_sum))

Classifier, ClassifierName SVC(gamma='auto') SVC
Feature set-1

/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.
  _warn_prf(average, modifier, msg_start, len(result))
/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.
  _warn_prf(average, modifier, msg_start, len(result))
/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.
  _warn_prf(average, "true nor predicted", "F-score is", len(true_sum))
/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.
  _warn_prf(average, modifier, msg_start, len(result))
/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.
  _warn_prf(average, modifier, msg_start, len(result))
/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.
  _warn_prf(average, "true nor predicted", "F-score is", len(true_sum))
/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.
  _warn_prf(average, modifier, msg_start, len(result))
/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.
  _warn_prf(average, modifier, msg_start, len(result))
/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.
  _warn_prf(average, "true nor predicted", "F-score is", len(true_sum))
/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.
  _warn_prf(average, modifier, msg_start, len(result))
/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.
  _warn_prf(average, modifier, msg_start, len(result))
/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.
  _warn_prf(average, "true nor predicted", "F-score is", len(true_sum))
/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.
  _warn_prf(average, modifier, msg_start, len(result))
/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.
  _warn_prf(average, modifier, msg_start, len(result))
/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.
  _warn_prf(average, "true nor predicted", "F-score is", len(true_sum))
/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.
  _warn_prf(average, modifier, msg_start, len(result))
/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.
  _warn_prf(average, modifier, msg_start, len(result))
/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.
  _warn_prf(average, "true nor predicted", "F-score is", len(true_sum))
/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.
  _warn_prf(average, modifier, msg_start, len(result))
/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.
  _warn_prf(average, modifier, msg_start, len(result))
/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.
  _warn_prf(average, "true nor predicted", "F-score is", len(true_sum))
/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.
  _warn_prf(average, modifier, msg_start, len(result))
/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.
  _warn_prf(average, modifier, msg_start, len(result))
/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.
  _warn_prf(average, "true nor predicted", "F-score is", len(true_sum))
/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.
  _warn_prf(average, modifier, msg_start, len(result))
/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.
  _warn_prf(average, modifier, msg_start, len(result))
/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.
  _warn_prf(average, "true nor predicted", "F-score is", len(true_sum))
/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.
  _warn_prf(average, modifier, msg_start, len(result))
/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.
  _warn_prf(average, modifier, msg_start, len(result))
/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.
  _warn_prf(average, "true nor predicted", "F-score is", len(true_sum))

Feature set-2

/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.
  _warn_prf(average, modifier, msg_start, len(result))
/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.
  _warn_prf(average, modifier, msg_start, len(result))
/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.
  _warn_prf(average, "true nor predicted", "F-score is", len(true_sum))
/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.
  _warn_prf(average, modifier, msg_start, len(result))
/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.
  _warn_prf(average, modifier, msg_start, len(result))
/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.
  _warn_prf(average, "true nor predicted", "F-score is", len(true_sum))
/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.
  _warn_prf(average, modifier, msg_start, len(result))
/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.
  _warn_prf(average, modifier, msg_start, len(result))
/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.
  _warn_prf(average, "true nor predicted", "F-score is", len(true_sum))
/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.
  _warn_prf(average, modifier, msg_start, len(result))
/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.
  _warn_prf(average, modifier, msg_start, len(result))
/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.
  _warn_prf(average, "true nor predicted", "F-score is", len(true_sum))
/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.
  _warn_prf(average, modifier, msg_start, len(result))
/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.
  _warn_prf(average, modifier, msg_start, len(result))
/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.
  _warn_prf(average, "true nor predicted", "F-score is", len(true_sum))
/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.
  _warn_prf(average, modifier, msg_start, len(result))
/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.
  _warn_prf(average, modifier, msg_start, len(result))
/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.
  _warn_prf(average, "true nor predicted", "F-score is", len(true_sum))
/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.
  _warn_prf(average, modifier, msg_start, len(result))
/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.
  _warn_prf(average, modifier, msg_start, len(result))
/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.
  _warn_prf(average, "true nor predicted", "F-score is", len(true_sum))
/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.
  _warn_prf(average, modifier, msg_start, len(result))
/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.
  _warn_prf(average, modifier, msg_start, len(result))
/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.
  _warn_prf(average, "true nor predicted", "F-score is", len(true_sum))
/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.
  _warn_prf(average, modifier, msg_start, len(result))
/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.
  _warn_prf(average, modifier, msg_start, len(result))
/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.
  _warn_prf(average, "true nor predicted", "F-score is", len(true_sum))
/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.
  _warn_prf(average, modifier, msg_start, len(result))
/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.
  _warn_prf(average, modifier, msg_start, len(result))
/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.
  _warn_prf(average, "true nor predicted", "F-score is", len(true_sum))

Feature set-3

/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.
  _warn_prf(average, modifier, msg_start, len(result))
/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.
  _warn_prf(average, modifier, msg_start, len(result))
/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.
  _warn_prf(average, "true nor predicted", "F-score is", len(true_sum))
/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.
  _warn_prf(average, modifier, msg_start, len(result))
/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.
  _warn_prf(average, modifier, msg_start, len(result))
/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.
  _warn_prf(average, "true nor predicted", "F-score is", len(true_sum))
/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.
  _warn_prf(average, modifier, msg_start, len(result))
/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.
  _warn_prf(average, modifier, msg_start, len(result))
/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.
  _warn_prf(average, "true nor predicted", "F-score is", len(true_sum))
/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.
  _warn_prf(average, modifier, msg_start, len(result))
/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.
  _warn_prf(average, modifier, msg_start, len(result))
/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.
  _warn_prf(average, "true nor predicted", "F-score is", len(true_sum))
/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.
  _warn_prf(average, modifier, msg_start, len(result))
/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.
  _warn_prf(average, modifier, msg_start, len(result))
/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.
  _warn_prf(average, "true nor predicted", "F-score is", len(true_sum))
/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.
  _warn_prf(average, modifier, msg_start, len(result))
/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.
  _warn_prf(average, modifier, msg_start, len(result))
/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.
  _warn_prf(average, "true nor predicted", "F-score is", len(true_sum))
/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.
  _warn_prf(average, modifier, msg_start, len(result))
/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.
  _warn_prf(average, modifier, msg_start, len(result))
/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.
  _warn_prf(average, "true nor predicted", "F-score is", len(true_sum))
/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.
  _warn_prf(average, modifier, msg_start, len(result))
/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.
  _warn_prf(average, modifier, msg_start, len(result))
/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.
  _warn_prf(average, "true nor predicted", "F-score is", len(true_sum))
/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.
  _warn_prf(average, modifier, msg_start, len(result))
/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.
  _warn_prf(average, modifier, msg_start, len(result))
/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.
  _warn_prf(average, "true nor predicted", "F-score is", len(true_sum))
/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.
  _warn_prf(average, modifier, msg_start, len(result))
/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.
  _warn_prf(average, modifier, msg_start, len(result))
/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.
  _warn_prf(average, "true nor predicted", "F-score is", len(true_sum))

Feature set-4

/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.
  _warn_prf(average, modifier, msg_start, len(result))
/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.
  _warn_prf(average, modifier, msg_start, len(result))
/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.
  _warn_prf(average, "true nor predicted", "F-score is", len(true_sum))
/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.
  _warn_prf(average, modifier, msg_start, len(result))
/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.
  _warn_prf(average, modifier, msg_start, len(result))
/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.
  _warn_prf(average, "true nor predicted", "F-score is", len(true_sum))
/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.
  _warn_prf(average, modifier, msg_start, len(result))
/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.
  _warn_prf(average, modifier, msg_start, len(result))
/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.
  _warn_prf(average, "true nor predicted", "F-score is", len(true_sum))
/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.
  _warn_prf(average, modifier, msg_start, len(result))
/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.
  _warn_prf(average, modifier, msg_start, len(result))
/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.
  _warn_prf(average, "true nor predicted", "F-score is", len(true_sum))
/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.
  _warn_prf(average, modifier, msg_start, len(result))
/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.
  _warn_prf(average, modifier, msg_start, len(result))
/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.
  _warn_prf(average, "true nor predicted", "F-score is", len(true_sum))
/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.
  _warn_prf(average, modifier, msg_start, len(result))
/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.
  _warn_prf(average, modifier, msg_start, len(result))
/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.
  _warn_prf(average, "true nor predicted", "F-score is", len(true_sum))
/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.
  _warn_prf(average, modifier, msg_start, len(result))
/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.
  _warn_prf(average, modifier, msg_start, len(result))
/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.
  _warn_prf(average, "true nor predicted", "F-score is", len(true_sum))
/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.
  _warn_prf(average, modifier, msg_start, len(result))
/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.
  _warn_prf(average, modifier, msg_start, len(result))
/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.
  _warn_prf(average, "true nor predicted", "F-score is", len(true_sum))
/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.
  _warn_prf(average, modifier, msg_start, len(result))
/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.
  _warn_prf(average, modifier, msg_start, len(result))
/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.
  _warn_prf(average, "true nor predicted", "F-score is", len(true_sum))
/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.
  _warn_prf(average, modifier, msg_start, len(result))
/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.
  _warn_prf(average, modifier, msg_start, len(result))
/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.
  _warn_prf(average, "true nor predicted", "F-score is", len(true_sum))

'''Read the value for one of the machine learning algorithm'''
file = os.path.join(ResultPathDir,f'{ClassifierName}.txt')
f = open(file, "r")
print(f.read())

Results for .Raw, .HARFeature, and selected features flag: False
ConfusionMatrix
[[467.   0.   0.   0.   0.]
 [  0.   0.   0.   0.   0.]
 [  0.   0.   0.   0.   0.]
 [  0.   0.   0. 169.  11.]
 [  1.   0.   0.  18. 179.]]

PrecissionValue
[0.99786325 0.         0.         0.90374332 0.94210526]

RecallValue
[1.         0.         0.         0.93888889 0.9040404 ]

F1ScoreValue
[0.99893048 0.         0.         0.92098093 0.92268041]

AccuracyValue
0.9644970414201184

Results for .Raw, .HARFeature, and selected features flag: True
ConfusionMatrix
[[467.   0.   0.   0.   0.]
 [  0.   0.   0.   0.   0.]
 [  0.   0.   0.   0.   0.]
 [  0.   0.   0. 172.   8.]
 [  0.   0.   0.  20. 178.]]

PrecissionValue
[1.         0.         0.         0.89583333 0.95698925]

RecallValue
[1.         0.         0.         0.95555556 0.8989899 ]

F1ScoreValue
[1.         0.         0.         0.92473118 0.92708333]

AccuracyValue
0.9668639053254438

Results for .Raw, .TransportFeatures, and selected features flag: False
ConfusionMatrix
[[467.   0.   0.   0.   0.]
 [  0.   0.   0.   0.   0.]
 [  0.   0.   0.   0.   0.]
 [  1.   0.   0. 167.  12.]
 [  1.   0.   0.   8. 189.]]

PrecissionValue
[0.99573561 0.         0.         0.95428571 0.94029851]

RecallValue
[1.         0.         0.         0.92777778 0.95454545]

F1ScoreValue
[0.99786325 0.         0.         0.94084507 0.94736842]

AccuracyValue
0.9739644970414201

Results for .Raw, .TransportFeatures, and selected features flag: True
ConfusionMatrix
[[467.   0.   0.   0.   0.]
 [  0.   0.   0.   0.   0.]
 [  0.   0.   0.   0.   0.]
 [  1.   0.   0. 171.   8.]
 [  0.   0.   0.  19. 179.]]

PrecissionValue
[0.99786325 0.         0.         0.9        0.95721925]

RecallValue
[1.        0.        0.        0.95      0.9040404]

F1ScoreValue
[0.99893048 0.         0.         0.92432432 0.92987013]

AccuracyValue
0.9668639053254438

Results for .Raw, .HARFeature, and selected features flag: False
ConfusionMatrix
[[4.668e+03 0.000e+00 0.000e+00 0.000e+00 0.000e+00]
 [0.000e+00 0.000e+00 0.000e+00 0.000e+00 0.000e+00]
 [0.000e+00 0.000e+00 0.000e+00 0.000e+00 0.000e+00]
 [3.000e+00 0.000e+00 0.000e+00 1.523e+03 2.710e+02]
 [2.000e+00 0.000e+00 0.000e+00 2.620e+02 1.713e+03]]

PrecissionValue
[0.99893162 0.         0.         0.85604504 0.86388957]

RecallValue
[1.         0.         0.         0.84747052 0.86640004]

F1ScoreValue
[0.99946524 0.         0.         0.85073667 0.8643697 ]

AccuracyValue
0.9362667208839281

Results for .Raw, .HARFeature, and selected features flag: True
ConfusionMatrix
[[4.668e+03 0.000e+00 0.000e+00 0.000e+00 0.000e+00]
 [0.000e+00 0.000e+00 0.000e+00 0.000e+00 0.000e+00]
 [0.000e+00 0.000e+00 0.000e+00 0.000e+00 0.000e+00]
 [4.000e+00 0.000e+00 0.000e+00 1.507e+03 2.860e+02]
 [3.000e+00 0.000e+00 0.000e+00 2.620e+02 1.712e+03]]

PrecissionValue
[0.99850791 0.         0.         0.85505239 0.85798841]

RecallValue
[1.         0.         0.         0.83854749 0.86590268]

F1ScoreValue
[0.99925225 0.         0.         0.84536249 0.86096787]

AccuracyValue
0.9342523626573935

Results for .Raw, .TransportFeatures, and selected features flag: False
ConfusionMatrix
[[4.668e+03 0.000e+00 0.000e+00 0.000e+00 0.000e+00]
 [0.000e+00 0.000e+00 0.000e+00 0.000e+00 0.000e+00]
 [0.000e+00 0.000e+00 0.000e+00 0.000e+00 0.000e+00]
 [2.000e+00 0.000e+00 0.000e+00 1.550e+03 2.450e+02]
 [4.000e+00 0.000e+00 0.000e+00 1.100e+02 1.863e+03]]

PrecissionValue
[0.99871931 0.         0.         0.93399167 0.88967268]

RecallValue
[1.         0.         0.         0.86260087 0.94230118]

F1ScoreValue
[0.99935852 0.         0.         0.89392584 0.91351202]

AccuracyValue
0.9572347794385708

Results for .Raw, .TransportFeatures, and selected features flag: True
ConfusionMatrix
[[4.668e+03 0.000e+00 0.000e+00 0.000e+00 0.000e+00]
 [0.000e+00 0.000e+00 0.000e+00 0.000e+00 0.000e+00]
 [0.000e+00 0.000e+00 0.000e+00 0.000e+00 0.000e+00]
 [3.000e+00 0.000e+00 0.000e+00 1.515e+03 2.790e+02]
 [2.000e+00 0.000e+00 0.000e+00 2.760e+02 1.699e+03]]

PrecissionValue
[0.99893117 0.         0.         0.84926891 0.85939022]

RecallValue
[1.         0.         0.         0.84301986 0.85931908]

F1ScoreValue
[0.99946501 0.         0.         0.84499994 0.8584157 ]

AccuracyValue
0.9336586836422782