测试数据集中的 CatBoostRegressor 拟合一条直线
第一张图是训练数据集(基于噪声罪训练的 CatBoostRegressor)第二张图是测试数据集
为什么它适合一条直线?其他功能相同(如 f(x)=x 等)
x = np.linspace(0, 2*np.pi, 100)
y = func(x) + np.random.normal(0, 3, len(x))
x_test = np.linspace(0*np.pi, 4*np.pi, 200)
y_test = func(x_test)
train_pool = Pool(x.reshape((-1,1)), y)
test_pool = Pool(x_test.reshape((-1,1)))
model = CatBoostRegressor(iterations=100, depth=2, loss_function="RMSE",
verbose=True
)
model.fit(train_pool)
y_pred = model.predict(x.reshape((-1,1)))
y_test_pred = model.predict(test_pool)
poly = Polynomial(4)
p = poly.fit(x,y);
plt.plot(x, y, 'ko')
plt.plot(x, func(x), 'k')
plt.plot(x, y_pred, 'r')
plt.plot(x, poly.evaluate(p, x), 'b')
plt.show()
plt.plot(x_test, y_test, 'k')
plt.plot(x_test, y_test_pred, 'r')
plt.show()
plt.plot(x_test, y_test, 'k')
plt.plot(x_test, poly.evaluate(p, x_test), 'b')
plt.show()