For helping Image processing & multiSVM & fitcsvm Error

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Özcan Atakan Tinmazlar 2022-1-9

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https://ww2.mathworks.cn/matlabcentral/answers/1625250-for-helping-image-processing-multisvm-fitcsvm-error

评论： Image Analyst 2022-1-9

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Hi

i'm working on a university project and i'm doing image processing.

So when i researching on google for my project content, i found some codes and tried but matlab gives an error.

This is the code I found to use multisvm but I want to ask you because I couldn't find clear explanatory information about this subject.

Here is the error

****************

Error using ClassificationSVM.prepareData (line 630)

Invalid data type. X must be a double or single matrix.

Error in classreg.learning.FitTemplate/fit (line 218)

this.PrepareData(X,Y,this.BaseFitObjectArgs{:});

Error in ClassificationSVM.fit (line 240)

this = fit(temp,X,Y);

Error in fitcsvm (line 343)

obj = ClassificationSVM.fit(X,Y,RemainingArgs{:});

Error in multisvm (line 29)

classes = predict(fitcsvm(svmStruct,tst,'KernelFunction','rbf'));

Error in mainproject (line 76)

result = multisvm(dataset,diseasetype,feature);

****************

As far as I understand the main cause of the error

svmStruct = fitcsvm(T,newClass);
classes = predict(fitcsvm(svmStruct,tst,'KernelFunction','rbf'));

Here is the code that i use

function [itrfin] = multisvm( T,C,test )
%Inputs: T=Training Matrix, C=Group, test=Testing matrix
%Outputs: itrfin=Resultant class
%C=str2num(cell2mat(C));
itrind=size(test,1);
itrfin=[];
Cb=C;
Tb=T;
for tempind=1:itrind
    tst=test(tempind,:);
    C=Cb;
    T=Tb;
    u=unique(C);
    N=length(u);
    c4=[];
    c3=[];
    j=1;
    k=1;
    if(N>2)
        itr=1;
        classes=0;
        cond=max(C)-min(C);
        while((classes~=1)&&(itr<=length(u))&& size(C,2)>1 && cond>0)
        %This while loop is the multiclass SVM Trick
            c1=(C==u(itr));
            newClass=c1;
            %svmStruct = fitcsvm(T,newClass,'kernel_function','rbf'); % I am using rbf kernel function, you must change it also
            svmStruct = fitcsvm(T,newClass);
            classes = predict(fitcsvm(svmStruct,tst,'KernelFunction','rbf'));
        
            % This is the loop for Reduction of Training Set
            for i=1:size(newClass,2)
                if newClass(1,i)==0
                    c3(k,:)=T(i,:);
                    k=k+1;
                end
            end
        T=c3;
        c3=[];
        k=1;
        
            % This is the loop for reduction of group
            for i=1:size(newClass,2)
                if newClass(1,i)==0
                    c4(1,j)=C(1,i);
                    j=j+1;
                end
            end
        C=c4;
        c4=[];
        j=1;
        
        cond=max(C)-min(C); % Condition for avoiding group 
                            %to contain similar type of values 
                            %and the reduce them to process
        
            % This condition can select the particular value of iteration
            % base on classes
            if classes~=1
                itr=itr+1;
            end    
        end
    end
valt=Cb==u(itr);		% This logic is used to allow classification
val=Cb(valt==1);		% of multiple rows testing matrix
val=unique(val);
itrfin(tempind,:)=val;  
end
end
% Give more suggestions for improving the program.

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Image Analyst 2022-1-9

I can't run it. You forgot to tell us what ( T,C,test ) are. Please tell us or attach them.

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