libuplift.meta.s_learner#

The S-learner meta model.

Simply add the treatment variable to a classifier/regressor.

Classes#

SLearnerUpliftRegressor

Mixin class for all uplift regression estimators in

SLearnerUpliftClassifier

Mixin class for all uplift classification estimators in

Module Contents#

class libuplift.meta.s_learner.SLearnerUpliftRegressor(base_estimator=LinearRegression(), treatment_encoding='one_hot')[source]#

Bases: libuplift.base.UpliftRegressorMixin, _SLearnerBase

Mixin class for all uplift regression estimators in libuplift.

predict(X)[source]#
class libuplift.meta.s_learner.SLearnerUpliftClassifier(base_estimator=LogisticRegression(), treatment_encoding='one_hot')[source]#

Bases: libuplift.base.UpliftClassifierMixin, _SLearnerBase

Mixin class for all uplift classification estimators in libuplift.

predict(X)[source]#