chapter_10.py 文件源码

def evaluate_decision_tree_regression(X, y):
    tree = DecisionTreeRegressor(max_depth=3)
    tree.fit(X, y)

    sort_index = X.flatten().argsort()

    lin_regplot(X[sort_index], y[sort_index], tree)
    plt.xlabel('% lower status of the population [LSTAT]')
    plt.ylabel("Price in $1000's [MEDV]")

    plt.show()