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

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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

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Accepted Answer

Yuvaraj Venkataswamy
Yuvaraj Venkataswamy on 27 Nov 2018
Edited: madhan ravi on 27 Nov 2018

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Oman Wisni
Oman Wisni on 27 Nov 2018
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 ?

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