当您使用 Dropout 时会发生这种情况，因为训练和测试时的行为不同.

This happens when you use Dropout, since the behaviour when training and testing are different.

在训练时，特征的百分比设置为零(在您的情况下为 50%，因为您使用的是 Dropout(0.5)).测试时，使用所有功能(并适当缩放).因此，测试时的模型更加稳健 - 并且可以带来更高的测试准确度.

When training, a percentage of the features are set to zero (50% in your case since you are using Dropout(0.5)). When testing, all features are used (and are scaled appropriately). So the model at test time is more robust - and can lead to higher testing accuracies.