清空筛选条件
清空筛选条件

Is there any way to add cross validation in trainingOptions function while using DNN?

4 次查看（过去 30 天）
Jhon Gray
Jhon Gray 2020-8-28
评论： Mohammad Sami 2020-8-30
Currently, I am training a CNN model to classify images. I am using splitEachLabel function to split the dataset into two segments. Training, validation. Then using augmentedImageDatastore for each set. Lastly using trainingOptions for setting the parameter and trainNetwork for training the model. Currently, the amount for validation is fixed in the dataset in every epoch (the fixed set of validation data is used). From my knowledge, this is called holdout validation approach.
I am wondering if it is possible to use k-fold corss validation approach rather than holdout validation while training a in deep neural network. If it's yes then how can I do it. How will I apply the dataset into k-fold?
TIA

请先登录，再回答此问题。

回答（1 个）

Mohammad Sami
Mohammad Sami 2020-8-30
There is no option for cross validation in training options for DNN.
  1 个评论
Mohammad Sami
Mohammad Sami 2020-8-30
With larger data set it may not be worth having k fold cross validation.
https://www.quora.com/Is-cross-validation-heavily-used-in-deep-learning-or-is-it-too-expensive-to-be-used

请先登录，再进行评论。

类别

在 Help Center 和 File Exchange 中查找有关 Deep Learning Toolbox 的更多信息

标签

产品


版本

R2020a

Community Treasure Hunt

Find the treasures in MATLAB Central and discover how the community can help you!

Start Hunting!

Translated by