这是过度拟合吗? [英] Is this overfitting?

问题描述

我的CNN在训练数据上的表现很好(准确度为96％，丢失1.％)，但在测试数据上的表现却很差(准确度为50％，丢失3.5％).

I have a CNN that is performing very well (96% accuracy, 1.~ loss) on training data but poorly (50% accuracy, 3.5 loss) on testing data.

推荐答案

过拟合的特征签名是指验证损失开始增加，而训练损失则继续减少，即:

The telltale signature of overfitting is when your validation loss starts increasing, while your training loss continues decreasing, i.e.:

(图片摘自Wikipedia上的过度拟合)

(Image adapted from Wikipedia entry on overfitting)

还有其他一些图表明过度拟合(源):

Here are some other plots indicating overfitting (source):

另请参见SO线程如何知道是否拟合不足还是过度拟合?.

很明显，您的损失图确实表现出了这种行为，所以是的，您确实过拟合了.

Clearly, your loss plot does exhibit such behavior, so yes, you are indeed overfitting.

相反，您在评论中链接到的图:

On the contrary, the plot you have linked to in a comment:

不会表现出这种行为，因此在这里并不是实际过拟合(您刚刚达到饱和点，超过此点验证错误就不会进一步改善).

does not exhibit such behavior, hence here you are not actually overfitting (you just have reached a saturation point, beyond which your validation error is not further improving).

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