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SimonBlanke / Hyperactive

An optimization and data collection toolbox for convenient and fast prototyping of computationally expensive models.
https://simonblanke.github.io/hyperactive-documentation
MIT License
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[ENH] `sklearn` compatible tuning wrapper estimator #85

Open fkiraly opened 1 month ago

fkiraly commented 1 month ago

I would suggest to expose the tuners as sklearn compatible tuning wrappers, e.g.,

HyperactiveCV(sklearn_estimator, config),

or

HyperactiveCV(sklearn_estimator, hyperopt_tuning_algo, config),

where HyperactiveCV inherits from sklearn BaseEstimator, and gets tested by parametrize_with_checks in the CI.

fkiraly commented 1 month ago

This is the estimator I'd use as a template: https://scikit-learn.org/stable/modules/generated/sklearn.model_selection.GridSearchCV.html

scikit-learn extension and API compliance testing guide: https://scikit-learn.org/stable/developers/develop.html