# Dataset x_train, x_test, y_train, y_test = iris() # x_train, x_test, y_train, y_test = digits() max_recall = np.zeros([4]) max_c = None fig_x = [x for x in range(-20, 20)] vis = Visualizer(num_x=len(fig_x)) for i, x in enumerate(fig_x): elm = MetricELM(hidden_num=4, c=2**x) elm.fit(x_train, y_train) recall = elm.validation(x_test, y_test) # visualization print("c=", x, "R@{1,2,4,8}:", np.around(recall, decimals=3)) vis.set(i, recall) # record max if recall[0] > max_recall[0]: max_recall = recall max_c = x print('best:') print("c=", max_c, "R@{1,2,4,8}:", np.around(max_recall, decimals=3)) vis.plot(x=fig_x, max_c=max_c, max_recall=max_recall) vis.show() # vis.save('resources/iris.png')