libuplift.meta.base#

Base classe for uplift meta models.

Classes#

UpliftMetaModelBase

Base class for uplift meta estimators.

Module Contents#

class libuplift.meta.base.UpliftMetaModelBase(base_estimator)[source]#

Bases: sklearn.utils.metaestimators._BaseComposition

Base class for uplift meta estimators.

Checks input consistency, builds classifiers on subsets of data.

Derived classess need to overwride the _get_model_names_list and _iter_training_subsets methods. The predict method needs to be implemented as well.

fit(X, y, trt, n_trt=None, sample_weight=None, **kwargs)[source]#
get_params(deep=True)[source]#

Get parameters for this estimator.

Parameters:
deepboolean, optional

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

Returns:
paramsmapping of string to any

Parameter names mapped to their values.

set_params(**kwargs)[source]#

Set the parameters of this estimator.

Valid parameter keys can be listed with get_params().

Returns:
self