绘制学习曲线 [Scikit Learn] - 如何设置 x 轴值/标签？

Question

我正在尝试使用它来绘制学习曲线。

http://scikit-learn.org/0.15/auto_examples/plot_learning_curve.html.

我想查看一组固定的训练规模。

所以在我手动设置的 plot_learning_curve 函数中。训练规模为 [10, 500, 1000, 2500, 5000]。但是，x 轴不会更新以在 x 轴上显示这些特定值。

def plot_learning_curve(estimator, title, X, y, ylim=None, cv=None,
                    n_jobs=1):

train_sizes = [10, 500, 1000, 2500, 5000]

plt.figure()
plt.title(title)
print(ylim)
if ylim is not None:
    plt.ylim(*ylim)
plt.xlabel("Training examples")
plt.ylabel("Score")
train_sizes, train_scores, test_scores = learning_curve(
    estimator, X, y, cv=cv, n_jobs=n_jobs, train_sizes=train_sizes)
train_scores_mean = np.mean(train_scores, axis=1)
train_scores_std = np.std(train_scores, axis=1)
test_scores_mean = np.mean(test_scores, axis=1)
test_scores_std = np.std(test_scores, axis=1)
plt.grid()


print(train_sizes)
plt.fill_between(train_sizes, train_scores_mean - train_scores_std,
                 train_scores_mean + train_scores_std, alpha=0.1,
                 color="r")
plt.fill_between(train_sizes, test_scores_mean - test_scores_std,
                 test_scores_mean + test_scores_std, alpha=0.1, color="g")
plt.plot(train_sizes, train_scores_mean, 'o-', color="r",
         label="Training score")
plt.plot(train_sizes, test_scores_mean, 'o-', color="g",
         label="Cross-validation score")

plt.legend(loc="best")
return plt

Image

你能看到它仍然显示 1000、2000、3000、4000、5000

Answer 1

使用xticks 参数

plt.plot(train_sizes, test_scores_mean, 'o-', color="g",
         label="Cross-validation score", xticks = train_sizes)