fitsearchcv 1.0.0

An extension to sklearn.GridSearchCV and RandomizedSearchCV to reduce over and underfitting

fitsearchcv— A smarter refit selector for scikit-learn searches

selector-mean is a tiny utility that helps reduce overfitting and underfitting when tuning hyperparameters with scikit-learn’s GridSearchCV or RandomizedSearchCV.

It provides a single function:

• selector_mean(cv_results_, metric=None, use_abs_gap=True, clip01=True)
  A callable you pass to refit=... that picks the parameter set balancing high test performance and small train–test gap.

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Why?

Vanilla GridSearchCV usually selects the highest mean test score, which can sometimes favor models with high variance.
selector_mean instead minimizes: 0.5 * (|train - test|) + 0.5 * (1 - test)