add_dummy_feature (original) (raw)

sklearn.preprocessing.add_dummy_feature(X, value=1.0)[source]#

Augment dataset with an additional dummy feature.

This is useful for fitting an intercept term with implementations which cannot otherwise fit it directly.

Parameters:

X{array-like, sparse matrix} of shape (n_samples, n_features)

Data.

valuefloat

Value to use for the dummy feature.

Returns:

X{ndarray, sparse matrix} of shape (n_samples, n_features + 1)

Same data with dummy feature added as first column.

Examples

from sklearn.preprocessing import add_dummy_feature add_dummy_feature([[0, 1], [1, 0]]) array([[1., 0., 1.], [1., 1., 0.]])