# 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')
