model_train_cv.py

mse  [] ## Regression Problem
accuracy_scores = []   ## Classification Problem

""" Train and Test Data Created Using Cross Validation"""
for train_index,test_index in kFold.split(X,y):
    X_train, X_test = X[train_index], X[test_index]
    y_train, y_test = y[train_index], y[test_index]
    
    print("Train Index:", train_index, "|", "Test Index:", test_index)
    
    
    ##### MODEL TRAINING #####
    model.fit(X_train,y_train)
    predictions = model.predict(X_test)  ## Predictions
    
    ##### MODEL VALIDATION ####
    """ Regression Problems """
    from sklearn.metrics import mean_squared_error
    mse.append(mean_squared_error(y_test,predictions))
    
    """ Classification Problems """
    accuracy_scores.append(accuracy_score(predictions,y_test))
   
""" Classification """
print('Accuracy Scores:', accuracy_scores)
print('Average Accuracy:', np.mean(accuracy_scores))

""" Regression """
print('MSE:', mse)
print('Average MSE:', np.mean(mse))