lale.lib.sklearn.polynomial_features module¶

class lale.lib.sklearn.polynomial_features.PolynomialFeatures(*, degree=2, interaction_only=False, include_bias=True, order='C')¶

Polynomial features transformer from scikit-learn.

This documentation is auto-generated from JSON schemas.

Parameters

degree (integer, >=2 for optimizer, <=3 for optimizer, optional, default 2) – The degree of the polynomial features.
interaction_only (boolean, optional, default False) – If true, only interaction features are produced: features that are products of at most degree distinct input features (so not x[1] ** 2, x[0] * x[2] ** 3, etc.).
include_bias (boolean, default True) – If True (default), then include a bias column, the feature in which all polynomial powers are zero (i.e. a column of ones - acts as an intercept term in a linear model).
order (‘C’ or ‘F’, optional, not for optimizer, default ‘C’) – Order of output array in the dense case. ‘F’ order is faster to compute, but may slow down subsequent estimators.

fit(X, y=None, **fit_params)¶

Train the operator.

Note: The fit method is not available until this operator is trainable.

Once this method is available, it will have the following signature:

Parameters

transform(X, y=None)¶

Transform the data.

Note: The transform method is not available until this operator is trained.

Once this method is available, it will have the following signature:

Parameters: X (array of items : array of items : float) – The data to transform, row by row.
Returns: result – The matrix of features, where NP is the number of polynomial
Return type: array of items : array of items : float