python-scikit-learnHow to split dataset to test and train samples

from sklearn import datasets, model_selection

X, y = datasets.load_diabetes(return_X_y=True)

X_train, X_test, y_train, y_test = model_selection.train_test_split(X, y, train_size=0.66)ctrl + cgithub

`from sklearn import` import module from scikit-learn	`datasets.load_diabetes` loads sample diabetes database
`model_selection.train_test_split` splits given `X` and `y` datasets to test (25% of values by default) and train (75% of values by default) subsets	`train_size` portion of objects to use for train sample (66% in our case)
`X_train, X_test` train and test samples for features	`y_train, y_test` train and test samples for target value

Usage example

from sklearn import datasets, model_selection

X, y = datasets.load_diabetes(return_X_y=True)

X_train, X_test, y_train, y_test = model_selection.train_test_split(X, y, train_size=0.66)

print(X_train.shape)
print(y_train.shape)
print(X_test.shape)
print(y_test.shape)

output

(291, 10)
(291,)
(151, 10)
(151,)

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