我想用一个函数来绘制两个机器学习模型的学习曲线。

def Learning_Curves(estimator,data1=input_data,data2=output_data,cv=5,train_sizes=train_sizes):    train_sizes,train_score,validation_score=learning_curve(estimator,data1,data2,cv=cv,train_sizes=train_sizes,shuffle=True)    mean_train_score=-train_score.mean(axis=1)    mean_validation_score=-validation_score(axis=1)    sns.lineplot(train_sizes,mean_train_score)    sns.lineplot(train_sizes,mean_validation_score)    plt.ylim(0,40)plt.figure(figsize = (16,5))   for model,i in zip([LinearRegression(),RandomForestRegressor()],[1,2]):                     plt.subplot(1,2,i)    Learning_Curves(model)

我不明白这个错误是什么意思。

回答：

你似乎忘记调用 validation_score.mean 了，在这里：

mean_validation_score = -validation_score(axis=1)

另外，你可以用这行代码替换原来的这行：

for model,i in zip([LinearRegression(),RandomForestRegressor()],[1,2]):

替换为

for i, model in enumerate((LinearRegression(),RandomForestRegressor()), start=1):