lale.lib.autogen.label_binarizer module

class lale.lib.autogen.label_binarizer.LabelBinarizer(*, neg_label=0, pos_label=1, sparse_output=False)

Bases: PlannedIndividualOp

Combined schema for expected data and hyperparameters.

This documentation is auto-generated from JSON schemas.

Parameters

  • neg_label (integer, >=0 for optimizer, <=1 for optimizer, uniform distribution, default 0) – Value with which negative labels must be encoded.

  • pos_label (integer, >=1 for optimizer, <=2 for optimizer, uniform distribution, default 1) – Value with which positive labels must be encoded.

  • sparse_output (boolean, default False) – True if the returned array from transform is desired to be in sparse CSR format.

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

y (union type) –

Target values

  • array of items : float

  • or array of items : array of items : float

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

y (union type) –

Target values

  • array of items : Any

  • or array of items : float

  • or array of items : array of items : float

Returns

result – Shape will be [n_samples, 1] for binary problems.

Return type

Any