f7a04171e58eb43dfe5b18d06c76481cdf1c5da9,deslib/dcs/lca.py,LCA,estimate_competence,#LCA#Any#Any#,85

Before Change

        dists, idx_neighbors = self._get_region_competence(query)
        competences = np.zeros(self.n_classifiers)

        for clf_index, clf in enumerate(self.pool_classifiers):
            // Check if the dynamic frienemy pruning (DFP) should be used used
            if self.DFP_mask[clf_index]:
                result = []
                predicted_label = predictions[clf_index]
                for index in idx_neighbors:
                    // Get only neighbors from the same class as predicted by the
                    // classifier (clf) to form the region of competence
                    if self.DSEL_target[index] == predicted_label:
                        result.append(self.processed_dsel[index][clf_index])

                if len(result) == 0:
                    competences[clf_index] = 0.0
                else:
                    competences[clf_index] = np.mean(result)

        return competences

After Change

        mask = (predictions_3d != target_3d)
        masked_preprocessed = np.ma.MaskedArray(self.processed_dsel[idx_neighbors, :], mask=mask)

        competences_masked = np.mean(masked_preprocessed, axis=1)
        // Fill 0 to the masked values in the resulting array (when no neighbors belongs to the class predicted by
        // the corresponding base classifier)
        competences = np.ma.filled(competences_masked, 0)

Instances