Invalid RHS for assignment to a categorical array.
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function [result] = multisvm(TrainingSet,Group_Train1,TestSet,actual_label)
%Models a given training set with a corresponding group vector and
%classifies a given test set using an SVM classifier according to a
%one vs. all relation.
%
%This code was written by Cody Neuburger cneuburg@fau.edu
%Florida Atlantic University, Florida USA...
%This code was adapted and cleaned from Anand Mishra's multisvm function
%found at http://www.mathworks.com/matlabcentral/fileexchange/33170-multi-class-support-vector-machine/
u=unique(Group_Train1);
numClasses=length(u);
result = categorical.empty();
%result = zeros(length(TestSet(:,1)),1);
%build models
models = cell(numClasses,1);
for k=1:numClasses
%Vectorized statement that binarizes Group
%where 1 is the current class and 0 is all other classes
G1vAll=(Group_Train1==u(k));
models{k} = fitcsvm(TrainingSet,G1vAll,'KernelFunction','polynomial','polynomialorder',3,'Solver','ISDA','Verbose',0,'Standardize',true);
if ~models{k}.ConvergenceInfo.Converged
fprintf('Training did not converge for class "%s"\n', string(u(k)));
end
end
%classify test cases
for t=1:size(TestSet,1)
matched = false;
for k = numClasses:-1:1
% for k =1: numClasses
if(predict(models{k},TestSet(t,: )))
matched = true;
break;
end
end
if matched
result(t,1) = u(k);
%result(t) = u(k);
else
result(t,1) = 'No Match';
%--------------------------------
end
end
%Accuracy = mean(Group_Test1==result) * 100;
%fprintf('Accuracy = %.2f\n', Accuracy);
%fprintf('error rate = %.2f\n ', mean(result ~= Group_Test1 ) * 100);
%confusionchart(Group_Test1, result);
end
>> HOG2
Error using categorical/subsasgn (line 72)
Invalid RHS for assignment to a categorical array.
Error in multisvm (line 52)
result(t,1) = u(k);
Error in HOG2 (line 30)
result= multisvm(Feat1,Group_Train1,Feat2,actual_label);
![](https://www.mathworks.com/matlabcentral/answers/uploaded_files/999970/image.png)
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采纳的回答
Jan
2022-5-16
Group_Train1 is a [274x1] double vector. u contains its unique elements. result is an empty categorical.
The error message means, that you cannot insert scalar doubles into an array of categoricals:
result = categorical.empty();
result(1) = 19 % FAIL
I'm confused by the different error message. Which Matlab version do you use?
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