cross validate does not have train_test_split
from sklearn.model_selection import train_test_splitcross validate does not have train_test_split
from sklearn.model_selection import train_test_splitsklearn cross validation score
from sklearn.model_selection import cross_val_score
scores = cross_val_score(classifier_logreg, X_train, y_train, cv = 5, scoring='accuracy')
print('Cross-validation scores:{}'.format(scores))
print('Average cross-validation score: {}'.format(scores.mean()))sklearn kfold
from sklearn.model_selection import GridSearchCV
from sklearn.model_selection import KFold
# Regressor
lrg = LinearRegression()
#Param Grid
param_grid=[{
'normalize':[True, False]
}]
# Grid Search with KFold, not shuffled in this example
experiment_gscv = GridSearchCV(lrg, param_grid,
cv=KFold(n_splits=4, shuffle=False),
scoring='neg_mean_squared_error')Copyright © 2021 Codeinu
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