kfold validation python code example

Example 1: sklearn split train test

import numpy as np
from sklearn.model_selection import train_test_split

X, y = np.arange(10).reshape((5, 2)), range(5)

X_train, X_test, y_train, y_test = train_test_split(
    X, y, test_size=0.33, random_state=42)

X_train
# array([[4, 5],
#        [0, 1],
#        [6, 7]])

y_train
# [2, 0, 3]

X_test
# array([[2, 3],
#        [8, 9]])

y_test
# [1, 4]

Example 2: how to import cross_validation from sklearn

from sklearn.model_selection import cross_validate

Example 3: 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')