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[FEATURE] Pass additional parameters to fit underlying estimator in `EstimatorTransformer`

See original GitHub issue

In EstimatorTransformer the underlying estimator is being fitted without the ability to pass along additional arguments to self.estimator_.fit.

This limits use cases for EstimatorTransformer. For example, if the underlying estimator is an XGBClassifier we would like to be able to pass eval_set to monitor validation performance and enable early stopping. This is currently not possible. Adding *args, **kwargs should fix this issue.

https://github.com/koaning/scikit-lego/blob/b4d087f0131ff164e6feebf238356ba6512b3635/sklego/meta/estimator_transformer.py#L31

Issue Analytics

State:
Created a year ago
Comments:14 (13 by maintainers)

Top GitHub Comments

2reactions

koaningcommented, Sep 12, 2022

TIL.

Yeah so if scikit-learn supports **kwargs then I won’t mind.

1reaction

koaningcommented, Sep 13, 2022

Ah! Crud. My bad.

I was confused with the Grouped variant of the meta estimators. These come with a predictor variant.

Please ignore the previous comment.

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