Grid5.py

#Logistic regression
from sklearn.linear_model import LogisticRegression

clf = LogisticRegression().fit(X_train,y_train)
y_pred = clf.predict(X_test)

# Model Evaluation metrics 
from sklearn.metrics import accuracy_score,recall_score,precision_score,f1_score
print('Accuracy Score : ' + str(accuracy_score(y_test,y_pred)))
print('Precision Score : ' + str(precision_score(y_test,y_pred)))
print('Recall Score : ' + str(recall_score(y_test,y_pred)))
print('F1 Score : ' + str(f1_score(y_test,y_pred)))

#Logistic Regression Classifier Confusion matrix
from sklearn.metrics import confusion_matrix
print('Confusion Matrix : \n' + str(confusion_matrix(y_test,y_pred)))