def intercluster_distance(ax=None): X, y = make_blobs(centers=12, n_samples=1000, n_features=16, shuffle=True) viz = InterclusterDistance(KMeans(9), ax=ax) viz.fit(X) viz.finalize() return viz
def distance_yellowbrick( X, y, features, ): plt.switch_backend('agg') plt.clf() X_train, X_test, y_train, y_test = train_test_split(X[features], y, stratify=y, test_size=0.01) X = pd.DataFrame(X_test, columns=features) y = pd.Series(y_test) n_clusters = y.nunique() model = MiniBatchKMeans(n_clusters) visualizer_dist = InterclusterDistance(model) visualizer_dist.fit(X) visualizer_dist.finalize() return plt