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Besides the default score method of our estimators, we should properly test and document the fact that one can use various metrics to evaluate our supervised and weakly-supervised metric learners when using sklearn's tools such as model_selection.GridSearchCV and model_selection.cross_val_score through their scoring parameter.
This should be done after dealing with #131, which will introduce a predict method for weakly supervised pairwise metric learners.
The text was updated successfully, but these errors were encountered:
Besides the default
score
method of our estimators, we should properly test and document the fact that one can use various metrics to evaluate our supervised and weakly-supervised metric learners when using sklearn's tools such asmodel_selection.GridSearchCV
andmodel_selection.cross_val_score
through theirscoring
parameter.This should be done after dealing with #131, which will introduce a predict method for weakly supervised pairwise metric learners.
The text was updated successfully, but these errors were encountered: