163eb7df13667e21b0e02a2706e18d1f53eee610,skrebate/vlsrelief.py,VLSRelief,fit,#VLSRelief#,65

Before Change

            print("features_scores_iter:")
            print(features_scores_iter)
            print("headers_iter:")
            print(headers_iter)
            print("features_selected:")
            print(features_selected)

After Change

        features_selected = []

        for iteration in range(self.num_feature_subset):
            if iteration == 1:
                // grab the previous features_selected
                // grab new features so that there is no overlap
                features_selected_id = []
                prev_selection = np.sort(features_selected[0])
                index = 0
                for i in range(total_num_features):
                    if index >= num_features:
                        features_selected_id.append(i)
                    elif prev_selection[index] != i:
                        features_selected_id.append(i)
                    else:
                        index += 1
            else:
                features_selected_id = np.random.choice(
                    range(total_num_features), num_features, replace=False)
                self.X_train = self.X_mat[:, features_selected_id]

            //print("features selected:")
            //print(features_selected_id)

            core_fit = core.fit(self.X_train, self._y)

            features_scores_iter.append(core_fit.feature_importances_)
            features_selected.append(features_selected_id)

Instances