Train Test Split

In Python, the train_test_split function, part of the sklearn.model_selection module, is frequently utilized for dividing a dataset into two parts: a training subset and a testing subset.

This train_test_split() function performs a random partitioning of the dataset into these subsets, determined by a predefined test size or train size.

Compito

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Split the dataset into training and test sets. Use only the first 1000 samples for splitting.
Print the shapes and sizes of the resulting training and test sets for both the feature matrix and the target vector.

Soluzione

from sklearn.model_selection import train_test_split

# Split the data

X_train, X_test, y_train, y_test = train_test_split(X[:1000], Y[:1000], test_size=1/7)

# Print the resulting shapes and sizes

print('TRAIN Feature matrix shape:', X_train.shape)

print('TRAIN Target vector size:', y_train.size)

print('TEST Feature matrix shape:', X_test.shape)

print('TEST Target vector size:', y_test.size)

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Sezione 1. Capitolo 6

AVAILABLE TO ULTIMATE ONLY