How to use fitcsvm in matlab classifications Brain tumor Mr image?(Benign,Malignant)

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load egitimseti.mat xdata = meas; group = label;
%svmStruct1 = svmtrain(xdata,group,'kernel_function', 'linear');
%Train the SVM Classifier
SVMModel= fitcsvm(meas,group,'KernelFunction','rbf','BoxConstraint',Inf);
sv = SVMModel.SupportVectors;
hold on
legend('MALIGNANT','BENIGN','Support Vector')
hold off
%species = svmclassify(svmStruct1,feat,'showplot',false
%x = fitcdiscr(xdata,group); label= predict(SVMModel,xdata);
%data1 = [meas(:,1),meas(:,2)]; %newfeat = [feat(:,1),feat(:,2)];
%close all
%SVMModel2=fitcsvm(data1,group); %label2=predict(SVMModel2,newfeat);
%En yüksek doğruluk(accurasy) icin trainset
data = meas; groups = ismember(label,'BENIGN'); groups = ismember(label,'MALIGNANT'); [train,test] = crossvalind('HoldOut',groups);%test ve egitim icin veriler karıstırıldı.0 ve 1 cp = classperf(groups);
%svmStruct = svmtrain(data(train,:),groups(train),'showplot',false,'kernel_function','linear');%yapi olustu%r %classes = svmclassify(svmStruct,data(test,:),'showplot',false);%svm ile sınıflandır SVMModelson=fitcsvm(data(train,:),groups(train)); class=predict(SVMModelson,data(test,:));
indicies = crossvalind('Kfold',label,10); cp = classperf(label);%for ;
%svmStruct = svmtrain(xdata(train,:),group(train),'boxconstraint',Inf,'showplot',false,'kernel_function','rbf');
%classes = svmclassify(svmStruct,xdata(test,:),'showplot',false);
%çapraz geçerlilik sonucu
Accuracy = cp.CorrectRate*100; sprintf("Dogruluk oranı %d dir",Accuracy);
Saad Rana
Saad Rana on 24 Jun 2022
The code gives an error for
load egitimseti.mat
xdata = meas;
group = label;
can you help me to create .mat file?

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Answers (1)

Bernhard Suhm
Bernhard Suhm on 20 Dec 2017
Can you illustrate what your data looks like, and where you get what type of error? And which release of MATLAB are you using? Looks like you were on an old release at first, since svmtrain has long been depracated.

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