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;
figure,
gscatter(xdata(:,1),xdata(:,2),group);
hold on
plot(sv(:,1),sv(:,2),'ko','MarkerSize',10)
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,:));
classperf(cp,class,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);
SVMModelnormalize=fitcsvm(xdata(train,:),group(train));
classes=predict(SVMModelnormalize,xdata(test,:));
classperf(cp,classes,test);
%end
%çapraz geçerlilik sonucu
Accuracy = cp.CorrectRate*100; sprintf("Dogruluk oranı %d dir",Accuracy);
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回答(1 个)

Bernhard Suhm
Bernhard Suhm 2017-12-20
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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