Randomly split data set and make sure that a sample of each class is included

Hello,

I am randomly splitting my dataset into train,validation and test sets as shown below:

% Random split Complete Data Set
Q = size(completeRDS,1);
Q1 = floor(Q*0.75);
Q2 = Q-Q1;
Q2 = round(Q2/2);
Q3 = Q2;

ind = randperm(Q);
ind1 = ind(1:Q1);
ind2 = ind(Q1+(1:Q2));
ind3 = ind(Q2+(1:Q3));

% Complete Data Set
trainData = completeRDS(ind1,1);
trainSeqLabels = seqLabels(ind1,1);
valData = completeRDS(ind3,1);
valLabels = seqLabels(ind3,1);
testData = completeRDS(ind2,1);
testLabels = seqLabels(ind2,1);

I have just realised that my test set has not included a sample from each class that I am trying to classify. It has not included 2 of the classes

How can i split my data set and make sure that the test set includes at least 1 sample of each class that i am trying to classify?

Thanks in advance

Answer 1

[MaryD]

If those are images I think best way is to load your data with class labels and then use splitEachLabel( __,'randomize') function.

[CHRISTOPHER MILLAR]

It is EMG signal data so i dont think this function will work

Thanks for your answer though