K-Fold Cross Validation

Hi Guys,

I have data of 36 users

as shown in the code (MATLAB) data is loaded into a matrix called Feat_Vec1

clear;
for nc = 1 : 36  % nc number of users
            % Load data into MATLAB
    data{nc} = load( sprintf('U%02d_Acc_TimeD_FreqD_FDay.mat', nc) );  

             % assign data into Matrix
      Feat_Vec1{nc} = data{nc}.Acc_TD_Feat_Vec(:,:);   

 end

for each user, I have 36 rows and 143 columns as a result, Feat_Vec1 contains 36 cells (number of users) and each cell contains 36 rows and 143 columns

I'd like to use 9-Fold Cross Validation in order to divide my dataset into training and testing.

First of all, 9-fold cross-validation means to user 8/9-th data for training and 1/9-th for testing. Repeat this nine times

I have seen this the documentation in MATLAB help but don't understand it!

I'm wondering if someone could help me please with the coding of 9-Fold Cross Validation for each user?

for examples:

for user1, 4 values from each column will be stored for testing and 32 values of each column will be used to train his model. This procedure will be repeated 9 times

Really appreciate any help

Regards.

[John Chilleri]

Hello,

What metric are you using?

K-Fold cross validation is pretty easy to code yourself, but what model are you fitting to the data (linear/quadratic/etc.)? And how would you like the testing set to be tested, perhaps the standard MSE?

[Swaroop Mishra]

Additionally, to reduce the coding effort, you can use Classification Learner App which is a part of Statistics and Machine Learning Toolbox.

In the Classification Learner App, you can select Data and Validation for Classification Problem