I want to combine some estimators, such as Logistic Regression, Gaussian NB and K-Nearest Neighbors for Features Selection, I tried to use StackingClassifier() estimator to do that, but there is no feature_importances_ attribute for this estimator.
Is there any other method to select features combining those classifiers ??
Thank you in advance :)
If you want to use a Stacking classifier I would recommend to change the feature selection algorithm to PermutationImportance, which is model agnostic way of computing importance based on random repeated permutation, but in this case you will have to provide a metric (accuracy, roc_auc, etc.) to measure the decrease on performance when a feature is shuffled, i.e the more the metric decreases when feature F is shuffled, the more important the feature is for the model.
