3e44c79a4254da2bf9972dccda44f50517393ad7,unbalanced_dataset/ensemble_sampling.py,BalanceCascade,resample,#BalanceCascade#,132

Before Change

            // Check if we have to make an early stopping
            if self.n_max_subset is not None:
                if self.n_max_subset >= n_subsets:
                    b_subset_search = False
                    if self.verbose:
                        print("The number of subset achieved their maximum")

            // Also check that we will have enough sample to extract at the
            // next round
            if n_elt_maj > np.count_nonzero(b_sel_N):
                b_subset_search = False
                // Select the remaining data
                idx_sel_from_maj = np.nonzero(b_sel_N)[0]

After Change

            // Check if we have to make an early stopping
            if self.n_max_subset is not None:
                if n_subsets == (self.n_max_subset - 1):
                    b_subset_search = False
                    // Select the remaining data
                    idx_sel_from_maj = np.nonzero(b_sel_N)[0]
                    idx_sel_from_maj = np.concatenate((idx_mis_class,
                                                   idx_sel_from_maj),
                                                  axis=0).astype(int)
                    // Select the final batch
                    x_data = np.concatenate((min_x, N_x[idx_sel_from_maj, :]), axis=0)
                    y_data = np.concatenate((min_y, N_y[idx_sel_from_maj]), axis=0)
                    // Push these data into a new subset
                    subsets_x.append(x_data)
                    subsets_y.append(y_data)
                    if self.verbose:
                        print("Creation of the subset //" + str(n_subsets))

                        // We found a new subset, increase the counter
                        n_subsets += 1
                    if self.verbose:
                        print("The number of subset achieved their maximum")

            // Also check that we will have enough sample to extract at the
            // next round
            if n_elt_maj > np.count_nonzero(b_sel_N):
                b_subset_search = False
                // Select the remaining data
                idx_sel_from_maj = np.nonzero(b_sel_N)[0]

Instances