plt.scatter(X_resampled[:,0], X_resampled[:,1], c=y_resampled) from imblearn.over_sampling import ADASYN ada=ADASYN(random_state=0, n_neighbors=5) X_resampled, y_resampled = ada.fit_resample(X,y) np.bincount(y_resampled) plt.scatter(X_resampled[:,0], X_resampled[:,1], c=y_resampled) from imblearn.under_sampling import NearMiss nm=NearMiss(version=1) nm.sample_indices=True X_resampled, y_resample = nm.fit_resample(X,y) np.bincount(y_resampled) plt.scatter(X_resampled[:,0], X_resampled[:,1], c=y_resampled) deleted_ind = np.setdiff1d(np.arange(len(X)), ind) plt.scatter(X[deleted_ind,0],X[deleted_ind,1],c=y[deleted_ind], marker='x', alpha=0.2 plt.scatter(X_resampled[:,0], X_resampled[:,1], c=y_resampled) from imblearn.under_sampling import OneSidedSelection oss=OneSidedSelection(random_state=0, n_neighbors=1, n_seeds_S=1)