CHANGELOG.rst

Changelog

0.11.0 (2024-09-05)

New features

• Add support for using scipy.sparse.csr_matrix as datastructure for covariates X.

0.10.0 (2024-08-13)

New features

• Add abstract method :meth:`~metalearners.metalearner.MetaLearner.predict_conditional_average_outcomes` to :class:`~metalearners.metalearner.MetaLearner`.
• Implement :meth:`~metalearners.rlearner.RLearner.predict_conditional_average_outcomes` for :class:`~metalearners.rlearner.RLearner`.

Bug fixes

• Fix bug in which the :class:`~metalearners.slearner.SLearner`'s inference step would have some leakage in the in-sample scenario.

0.9.0 (2024-08-02)

New features

• Add :meth:`metalearners.metalearner.MetaLearner.init_args`.
• Add :class:`metalearners.utils.FixedBinaryPropensity`.
• Add _build_onnx to :class:`metalearners.MetaLearner` abstract class and implement it for :class:`metalearners.TLearner`, :class:`metalearners.XLearner`, :class:`metalearners.RLearner` and :class:`metalearners.DRLearner`.
• Add _necessary_onnx_models to :class:`metalearners.MetaLearner`.
• Add :meth:`metalearners.metalearner.DRLearner.average_treatment_effect` to compute the AIPW point estimate and standard error for _average treatment effects (ATE)_ without requiring a full model fit.

0.8.0 (2024-07-22)

New features

• Add :meth:`metalearners.metalearner.MetaLearner.fit_all_nuisance` and :meth:`metalearners.metalearner.MetaLearner.fit_all_treatment`.
• Add optional store_raw_results and store_results parameters to :class:`metalearners.grid_search.MetaLearnerGridSearch`.
• Renamed :class:`metalearners.grid_search._GSResult` to :class:`metalearners.grid_search.GSResult`.
• Added grid_size_ attribute to :class:`metalearners.grid_search.MetaLearnerGridSearch`.
• Implement :meth:`metalearners.cross_fit_estimator.CrossFitEstimator.score`.

Bug fixes

• Fixed a bug in :meth:`metalearners.metalearner.MetaLearner.evaluate` where it failed in the case of feature_set being different from None.

0.7.0 (2024-07-12)

New features

• Add optional adaptive_clipping parameter to :class:`metalearners.DRLearner`.

Other changes

• Change the index columns order in MetaLearnerGridSearch.results_.
• Raise a custom error if only one class is present in a classification outcome.
• Raise a custom error if there are some treatment variants which have seen classification outcomes which have not appeared for some other treatment variant.

0.6.0 (2024-07-08)

New features

• Implement :class:`metalearners.grid_search.MetaLearnerGridSearch`.
• Add a scoring parameter to :meth:`metalearners.metalearner.MetaLearner.evaluate` and implement the abstract method for the :class:`metalearners.XLearner` and :class:`metalearners.DRLearner`.

Other changes

• Increase lower bound on scikit-learn from 1.3 to 1.4.
• Drop the run dependency on git_root.

0.5.0 (2024-06-18)

• No longer raise an error if feature_set is provided to :class:`metalearners.SLearner`.
• Fix a bug where base model dictionaries -- e.g. n_folds or feature-set -- were improperly initialized if the provided dictionary's keys were a strict superset of the expected keys.

0.4.2 (2024-06-18)

• Ship license file.

0.4.1 (2024-06-18)

• Fix dependencies for pip.

0.4.0 (2024-06-18)

• Implemented :meth:`metalearners.cross_fit_estimator.CrossFitEstimator.clone`.
• Added n_jobs_base_learners to :meth:`metalearners.metalearner.MetaLearner.fit`.
• Renamed :meth:`metalearners.explainer.Explainer.feature_importances`. Note this is a breaking change.
• Renamed :meth:`metalearners.metalearner.MetaLearner.feature_importances`. Note this is a breaking change.
• Renamed :meth:`metalearners.explainer.Explainer.shap_values`. Note this is a breaking change.
• Renamed :meth:`metalearners.metalearner.MetaLearner.shap_values`. Note this is a breaking change.
• Renamed :meth:`metalearners.metalearner.MetaLearner.explainer`. Note this is a breaking change.
• Implemented synchronize_cross_fitting parameter for :meth:`metalearners.metalearner.MetaLearner.fit`.
• Implemented cv parameter for :meth:`metalearners.cross_fit_estimator.fit`.

0.3.0 (2024-06-03)

• Implemented :class:`metalearners.explainer.Explainer` with support for binary classification and regression outcomes and discrete treatment variants.
• Integration of :class:`metalearners.explainer.Explainer` with :class:`metalearners.metalearner.MetaLearner` for feature importance and SHAP values calculations.
• Implemented model reusage through the fitted_nuisance_models and fitted_propensity_model parameters of :class:`metalearners.metalearner.MetaLearner`.
• Allow for fit_params in :meth:`metalearners.metalearner.MetaLearner.fit`.

0.2.0 (2024-05-28)

Beta release with

• :class:`metalearners.DRLearner` with support for binary classification and regression outcomes and discrete treatment variants.
• Generalization of :class:`metalearners.TLearner`, :class:`metalearners.XLearner` and :class:`metalearners.RLearner` to allow for more than two discrete treatment variants.
• Unification of shapes returned by predict methods.
• :func:`metalearners.utils.simplify_output` and :func:`metalearners.utils.metalearner_factory`.

0.1.0 (2024-05-16)

Alpha release with

• :class:`metalearners.TLearner` with support for binary classification and regression outcomes and binary treatment variants.
• :class:`metalearners.SLearner` with support for binary classification and regression outcomes and discrete treatment variants.
• :class:`metalearners.XLearner` with support for binary classification and regression outcomes and binary treatment variants.
• :class:`metalearners.RLearner` with support for binary classification and regression otucomes and binary treatment variants.