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Description
For now only strings are accepted as the measures
parameter in GridSearchCV
, RandomizedSearchCV
, and cross_validate
. It's thus impossible to use those with measures that take specific parameters as input (e.g. #156 ), or to use custom measures.
We should then accept callables in addition to strings.
Each callable should only take the predictions
parameter. In order to handle measures with mulptile parameters, we could implement a make_measure
helper (much like sklearn make_scorer) which would simply perform some partial application on the parameters, and set a greater_is_better
parameter (this would clean a bit the current code).
Any other option is welcome