测试/验证集中的数据扩充? [英] Data augmentation in test/validation set?

问题描述

通常的做法是在训练和测试集或仅在训练数据集上扩充数据(以编程方式添加样本，例如，随机作物等，如果图像由图像组成)?

It is common practice to augment data (add samples programmatically, such as random crops, etc. in the case of a dataset consisting of images) on both training and test set, or just the training data set?

推荐答案

仅在培训中.数据增强用于增加训练集的大小并获得更多不同的图像. 从技术上讲，您可以在测试集上使用数据增强来查看模型在此类图像上的行为，但通常人们不这样做.

Only on training. Data augmentation is used to increase the size of training set and to get more different images. Technically, you could use data augmentation on test set to see how model behaves on such images, but usually people don't do it.

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