ExtLabelEncoder

class skactiveml.utils.ExtLabelEncoder(classes=None, missing_label=nan, target_type='single-output')

Bases: BaseEstimator

Encode class labels with integers in [0, …, n_classes-1] and use -1 for unlabeled.

Parameters:

classesarray-like of shape (n_classes,) or a list of such array-likes, default=None

• If classes is not nested (None or one-dimensional), a single task problem is assumed such that y can be shape (n_samples,) or (n_samples, n_annotators). Same encoder is applied to all entries.

• If classes is nested, target_type must be “multi-label”, and y must contain one column per binary class vocabulary.

missing_labelscalar or string or np.nan or None, default=np.nan

Value to represent a missing label.

target_type“single-output” or “multi-label”, default=”single-output”

Resolved target type controlling whether one shared encoder or one encoder per label is used.

Methods

fit(y)	Fit label encoder.
fit_transform(y)	Fit label encoder and return encoded labels.
inverse_transform(y)	Transform labels back to original encoding.
transform(y)	Transform labels to new class encoding.
get_metadata_routing()	Get metadata routing of this object.
get_params([deep])	Get parameters for this estimator.
set_params(**params)	Set the parameters of this estimator.

ExtLabelEncoder.fit(y)

Fit label encoder.

Parameters:

yarray-like of shape (n_samples,) or (n_samples, n_outputs)

Class labels.

Returns:

selfExtLabelEncoder

Returns an instance of ExtLabelEncoder.

ExtLabelEncoder.fit_transform(y)

Fit label encoder and return encoded labels.

Parameters:

yarray-like of shape (n_samples,) or (n_samples, n_outputs)

Class labels.

Returns:

ynp.ndarray shape (n_samples,) or (n_samples, n_outputs)

Class labels.

ExtLabelEncoder.inverse_transform(y)

Transform labels back to original encoding.

Parameters:

ynumpy array of shape (n_samples,) or (n_samples, n_outputs)

Encoded class labels.

Returns:

y_decnp.ndarray of shape (n_samples,) or (n_samples, n_outputs)

Decoded (original) class labels.

ExtLabelEncoder.transform(y)

Transform labels to new class encoding.

Parameters:

yarray-like of shape (n_samples,) or (n_samples, n_outputs)

Original class labels.

Returns:

y_encarray-like of shape (n_samples) or (n_samples, n_outputs)

Encoded class labels.

ExtLabelEncoder.get_metadata_routing()

Get metadata routing of this object.

Please check User Guide on how the routing mechanism works.

Returns:

routingMetadataRequest

A MetadataRequest encapsulating routing information.

ExtLabelEncoder.get_params(deep=True)

Get parameters for this estimator.

Parameters:

deepbool, default=True

If True, will return the parameters for this estimator and contained subobjects that are estimators.

Returns:

paramsdict

Parameter names mapped to their values.

ExtLabelEncoder.set_params(**params)

Set the parameters of this estimator.

The method works on simple estimators as well as on nested objects (such as Pipeline). The latter have parameters of the form <component>__<parameter> so that it’s possible to update each component of a nested object.

Parameters:

**paramsdict

Estimator parameters.

Returns:

selfestimator instance

Estimator instance.