PYTHON QUESTION I am running this code to answer this question using theparkingson data. I get the

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PYTHON QUESTION

I am running this code to answer this question using theparkingson data. I get the error below. can someone help me troubleshoot 1. Use cross-validation to build a linear regression model topredict total_UPDRS #################### import os import pandas aspd from sklearn.model_selection import train_test_split importsklearn.metrics as metrics import matplotlib.pyplot as plt############################################################################## Regression models path =r"C:UsersrobrDesktopSchoolweek9"os.chdir(path) parking =pd.read_csv("parking.csv") parking.head() parking.sex.describe() #Train_test split X = parking.loc[:,['subject#', 'age', 'sex','test_time', 'Jitter(%)', 'Jitter(Abs)','Jitter:RAP', 'Jitter:PPQ5', 'Jitter:DDP', 'Shimmer', 'Shimmer(dB)', 'Shimmer:APQ3', 'Shimmer:APQ5','Shimmer:APQ11', 'Shimmer:DDA', 'NHR','HNR', 'RPDE', 'DFA', 'PPE']] y = parking.total_UPDRS X.describe()y.describe() X_train, X_test, y_train, y_test = train_test_split(X,y, test_size = 0.3, random_state = 123) from sklearn import linear_modellreg = linear_model.LinearRegression().fit(X_train, y_train)lreg.score(X_train, y_train) lreg.score(X_test, y_test)################### #cross validation from sklearn.model_selectionimport cross_val_score # Use linear Reg as the classifier lreg =linear_model.LinearRegression() accuracies = cross_val_score(lreg,X_train, y_train, cv = 10) accuraciespd.Series(accuracies).describe() ################### fromsklearn.model_selection import cross_validate scoring =['accuracy'] scores = cross_validate(lreg, X_train, y_train,scoring = scoring, cv = 10, return_train_score =True) ########################## ERROR RETURNED File"C:Usersrobanaconda3libsite-packagessklearnmetricsclassification.py",line 88, in _check_targets raise ValueError("{0} isnot supported".format(y_type)) ValueError: continuous is notsupported