can I see testing accuracy and loss graph in Neural network, like training graph?

4 次查看（过去 30 天）

krishna Chauhan 2020-7-22

0
链接

此问题的直接链接

https://ww2.mathworks.cn/matlabcentral/answers/568962-can-i-see-testing-accuracy-and-loss-graph-in-neural-network-like-training-graph

评论： krishna Chauhan 2020-9-13

In classify() function can i set parameters to plot graph for testing accuracy and loss?

also what if I have not provided any validation data ie i have done two partions only training and test. Is there any problem?

0 个评论
显示 -2更早的评论隐藏 -2更早的评论

请先登录，再进行评论。

请先登录，再回答此问题。

采纳的回答

Raunak Gupta 2020-8-12

0
链接

此回答的直接链接

https://ww2.mathworks.cn/matlabcentral/answers/568962-can-i-see-testing-accuracy-and-loss-graph-in-neural-network-like-training-graph#answer_478455

Hi Krishna,

I assume by graph of the testing accuracy and loss; you mean epoch wise plot of the parameters for testing data. I think if you want to get the values for the testing data it is required to pass the data while training itself so that prediction can be made at every epoch and accordingly mini-batch accuracy and loss can be updated.

So essentially you need to pass testing data as validation data for calculating the accuracy and loss epoch wise.

For second question, it is completely fine to skip the validation data.

Hope this clarifies.

7 个评论
显示 5更早的评论隐藏 5更早的评论

Raunak Gupta 2020-9-11

Hi,

What is the typical difference you are seeing between different runs? If the difference is small, it may be due to the shuffling of the training data that happens between every epoch or at the very start of the training.

You may set the 'Shuffle' Name-value pair in trainingOptions to 'never' if this is the issue.

krishna Chauhan 2020-9-13