Best way to split data into random partitions

I have a mat file which contains a double that I created into a histogram.

I have classOne and classTwo. I am trying to slip the data into random partitions

this is not working for me. can you help?

split = [x,y];

% Cross varidation (train: 70%, test: 30%)

cv = cvpartition(split,'HoldOut',0.4);

idx = cv.test;

% Separate to training and test data

dataTrain = split(~idx,:);

dataTest = split (idx,:);

[Akira Agata]

What is the variable split ? If this variable is a data set with N-by-M array, I think the following will work.

split = [x,y]; 
% Cross varidation (train: 70%, test: 30%)
cv = cvpartition(size(split,1),'HoldOut',0.3);
idx = cv.test;
% Separate to training and test data
dataTrain = split(~idx,:);
dataTest  = split (idx,:);

[madhan ravi]

isn’t https://www.mathworks.com/matlabcentral/answers/439417-best-way-to-split-data-into-random-partitions the same?

Answer 1

[Asimananda Khandual]

if you have 15 dataset feed as variable Lab_ABC to split for training and testing proceed as below:

Indices=randperm(15);

Trainingset=Lab_ABC(Indices(1:10),:);

Testingset= Lab_ABC (Indices(11:end),:);

Asim