BPt.EvalResultsSubset.feat_names

property EvalResultsSubset.feat_names

The features names corresponding to any measures of feature importance, stored as a list of lists, where the top level list represents each fold of cross validation.

This parameter may be especially useful when pipeline objects such as transformers or feature selectors are used as these can drastically change the features passed to an eventual model.

The values stored here may change based on the passed value of the decode_feat_names parameter from evaluate().

For example the feat_names from a 3-fold cross-validation with input features [‘feat1’, ‘feat2’, ‘feat3’] with feature selection as a piece of the pipeline may look like:

self.feat_names = [['feat1', 'feat2'],
                   ['feat2', 'feat3'],
                   ['feat1', 'feat2']]