Best way to split data into random partitions
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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,:);
2 个评论
Akira Agata
2019-1-13
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,:);
回答(1 个)
Asimananda Khandual
2020-8-4
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
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