help with error in my code
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Hi can someone help me understand the mistake in my code, i followed the correct syntax from https://uk.mathworks.com/help/bioinfo/ref/classperf.html
i keep getting the error
operator "==" not supported for operands of type "cvpartition"
error in line 24
test = (indices == 1)
k = 4;
n = 699; %sample lenght
rng ('default')
indices = cvpartition(n,'kfold', k);
for i = 1:k
test= (indices == i); train = ~test;
class = classify(InputVariable(test,:),InputVariable(train,:),OutputVariable(train,:));
classperf(cp,class,test);
end
cp.ErrorRate
plotconfusion(testTarget, testY)
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Stephen23
2021년 1월 2일
편집: Stephen23
2021년 1월 2일
Original question by Dilpreet kaur retrieved from Google Cache:
help with error in my code
Hi can someone help me understand the mistake in my code, i followed the correct syntax from https://uk.mathworks.com/help/bioinfo/ref/classperf.html
i keep getting the error
operator "==" not supported for operands of type "cvpartition"
error in line 24
test = (indices == 1)
k = 4;
n = 699; %sample lenght
rng ('default')
indices = cvpartition(n,'kfold', k);
for i = 1:k
test= (indices == i); train = ~test;
class = classify(InputVariable(test,:),InputVariable(train,:),OutputVariable(train,:));
classperf(cp,class,test);
end
cp.ErrorRate
plotconfusion(testTarget, testY)
채택된 답변
Image Analyst
2020년 12월 31일
I get this:
k = 4;
n = 699; %sample lenght
rng ('default')
indices = cvpartition(n,'kfold', k)
indices =
K-fold cross validation partition
NumObservations: 699
NumTestSets: 4
TrainSize: 525 524 524 524
TestSize: 174 175 175 175
You're not using indices correctly. It's an object, not a list of indices. If you want a listof indices, use randperm().
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추가 답변 (1개)
Walter Roberson
2021년 1월 1일
편집: Walter Roberson
2021년 1월 2일
cvpartition does not return indices.
rng ('default')
nfold = 4;
cvfolds = cvpartition(699,'kfold', nfold);
cp = classperf(OutputVariable); % initializes the CP object
for i = 1:nfold
test = cvfolds.test(i);
train = cvfolds.training(i);
class = classify(InputVariable(test,:), InputVariable(train,:), OutputVariable(train,:));
classperf(cp, class, test);
end
cp.ErrorRate
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