why my models testing accuracy gets worse

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uma 2022-6-23

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https://ww2.mathworks.cn/matlabcentral/answers/1746575-why-my-models-testing-accuracy-gets-worse

waveform.csv

I have written my code below and dataset is also attached. After applyng the 10 fold cross-validation, the testing accuracy gets worse while there is no problem in training accuracy. Please help me to resovle this issue.

data1=xlsread('waveform.csv');

data=data1(:,1:end);

groups=data1(:,end);

Fold=10;

indices = crossvalind('Kfold',length(groups),Fold); % create indices of 10 fold cross-validation, Group is the vector containing the class label for each obsevation

for i =1:Fold % create train and test sets

display(['cross validation, folds' num2str(i)])

testy = (indices == i);

trainy = (~testy);

TrainInputData=data(trainy,:);

TrainOutputData=groups(trainy,:);

TestInputData=data(testy,:);

TestOutputData=groups(testy,:);

% set the parameters

% regularization parameter: [C1, C2, C3] for each layer respectively

% kernel parameters: [SIG1, SIG2, SIG3] for each layer respectively

C1 = 1; C2 = 1; C3 = 1;