econml.grf.MultiOutputGRF

class econml.grf.MultiOutputGRF(estimator)[source]

Bases: sklearn.base.BaseEstimator

Simple wrapper estimator that enables multiple outcome labels for all the grf estimators that only accept a single outcome. Similar to MultiOutputRegressor.

__init__(estimator)[source]

Methods

`__init__`(estimator)
`feature_importances`([max_depth, ...])
`fit`(X, T, y, *[, sample_weight])
`get_params`([deep])	Get parameters for this estimator.
`oob_predict`(Xtrain)
`predict`(X[, interval, alpha])
`predict_and_var`(X)
`predict_projection_and_var`(X, projector)
`set_params`(**params)	Set the parameters of this estimator.

Attributes

feature_importances_

get_params(deep=True)

Get parameters for this estimator.

Parameters: deep (bool, default=True) – If True, will return the parameters for this estimator and contained subobjects that are estimators.
Returns: params – Parameter names mapped to their values.
Return type: dict

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: **params (dict) – Estimator parameters.
Returns: self – Estimator instance.
Return type: estimator instance