lale.lib.autogen.binarizer module

class lale.lib.autogen.binarizer.Binarizer(*, threshold=0.0, copy=True)

Bases: PlannedIndividualOp

Combined schema for expected data and hyperparameters.

This documentation is auto-generated from JSON schemas.

Parameters

  • threshold (float, not for optimizer, default 0.0) – Feature values below or equal to this are replaced by 0, above it by 1

  • copy (boolean, default True) – set to False to perform inplace binarization and avoid a copy (if the input is already a numpy array or a scipy.sparse CSR matrix).

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

X (array of items : Any) –

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 binarize, element by element

  • y (Any, optional) –

  • copy (boolean, optional) – Copy the input X or not.

Returns

result – Binarize each element of X

Return type

Any