How create training and testing data with k-fold validation using neural network ?

Hi, I have finished training and testing data with the neural network formula that I calculated manually. Where is my data x = input (275x25) and t = target (275x1). Now I want to partition my data using K-fold validation where k = 5.

If I make (train or test) it manually, I have to train the input.mat data for the training, which consists of five files with dimension 220x25 every file.mat and five input.mat data for test with dimension 55x25 . I do this by inputting or loading the file repeatedly.

How can I implement the k-fold in the neural network code that I created? Is that possible, do the training and testing partitions then each data partition results in the accuracy of each partition both training and test?

please help me, I confused how where I should put code for k-fold. May anyone help some clear steps to explain it? Thanks

Answer 1

[Yuvaraj Venkataswamy]

K-fold cross validation you can use,

https://www.mathworks.com/help/stats/cvpartition.test.html,

https://www.mathworks.com/help/stats/cvpartition.training.html

for training.

[Oman Wisni]

There are tutorial how create cross valitadion. should I partition first and then training or what?

input = inputs;
target =targets;
k=5;
cvFolds = crossvalind('Kfold');

How I create in cv ? can give me example ?