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SelectFromModel score extention #579
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What about also a function which will merge selected features columns names with the feature_importances_ or coef_ value? As I always need to perform that manually by adding some code like:
X_train_coef.columns = X_train.columns[(sel_.get_support())] # Join ABS of Coefs with features coef_table.rename(columns={0: "Feature"}, inplace=True) |
It would be great to have a feature which extends from class sklearn.feature_selection.SelectFromModel and allows us to review the score of the base estimator from which the transformer is built,
Something like feature_engine.sel_.score
That will help to undertand the score of the model used to select the features, as it is not the same to select A and B from a model that scores 0.5 than other features from a model which scores 0.97.
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