85d5c30d2186d07857d1f0fb7c269eb08d2b7d79,deslib/des/des_clustering.py,DESClustering,fit,#DESClustering#,96

Before Change

            // Compute accuracy of each classifier in this cluster
            prediction_matrix = np.zeros((len(targets), self.n_classifiers))
            for clf_index in range(self.n_classifiers):
                predictions = self.BKS_dsel[sample_indices, clf_index]
                prediction_matrix[:, clf_index] = predictions
                // Check if the dynamic frienemy pruning (DFP) should be used used
                self.accuracy_cluster[cluster_index][clf_index] = accuracy_score(np.array(targets), predictions)

            // Get the N most accurate classifiers for the corresponding cluster
            accuracies = self.accuracy_cluster[cluster_index, :]
            accuracy_indices = np.argsort(accuracies)[::-1][0:self.N]

            self.diversity_cluster[cluster_index, :] = self._compute_diversity(targets, prediction_matrix)

After Change

            sample_indices = np.where(labels == cluster_index)[0]

            // Compute accuracy of each classifier in this cluster
            accuracy = np.mean(self.processed_dsel[sample_indices, :], axis=0)
            self.accuracy_cluster[cluster_index, :] = accuracy

            // Get the N most accurate classifiers for the corresponding cluster
            accuracy_indices = np.argsort(accuracy)[::-1][0:self.N]

Instances