Not enough input arguments

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Feyza Zehra Asik
Feyza Zehra Asik el 16 de Oct. de 2021
Respondida: yanqi liu el 27 de Dic. de 2021
I'm very new to MATLAB and I am having some trouble. It says error using predict (line 70) Not enough input arguments. It gives this error for line [c_matrix,Result,RefereceResult]= confusion.getMatrix(actual,predict);
load veri.mat
load etiket.mat
figure;
plot(veri(1,:))
%özellik çıkarımı
for i=1:length(etiket)
x=veri(i,:);
ozellik(1,i)=(1/length(x))*sum(x.^2); %enerji
ozellik(2,i)=std(x); %standart
ozellik(3,i)=mean(abs(x)); %mutlak değerin ortalamaası
ozellik(4,i)=skewness(x); %agirlik
ozellik(5,i)=kurtosis(x); %basiklik
end
%4 katli capraz doğrulama
fold=cvpartition(etiket, 'kfold',4);
label=etiket;
%egitim ve test idelerinin ayrilmasi
trainIdx=fold.training(1); testIdx=fold.test(1);
%egitim verisinin ayrilmasi
Xtrain=ozellik(:,trainIdx); Ytrain=label(trainIdx);
%test verisinin ayrilmasi
Xtest=ozellik(:,testIdx); Ytest=label(testIdx);
%DVM Tasarımı
%cekridek fonksiyonu seçimi
t= templateSVM('Standardize',true, 'KernelFunction','gaussian');
%model eğitim
giris=transpose(Xtrain);
SVMModel = fitcecoc(giris,Ytrain,'Learners',t,'FitPosterior',true,...
'Classnames', {'Sag','Swell', 'Flicker'})
%model test islemi
predict_label = predict(SVMModel,transpose(Xtest));
predict_label = (categorical(cellstr(predict_label)));
for i=1: length(Ytest)
if Ytest(i,1)=='sag'
actual(1,i)=1;
end
if Ytest(i,1)=='Swell'
actual(1,i)=2;
end
if Ytest(i,1)=='Flicker'
actual(1,i)=3;
end
i
end
[c_matrix,Result,RefereceResult]= confusion.getMatrix(actual,predict);
%es olusum matrisinin gösterimi
figure;
cm= confusionchart(Ytest, predict_label,'RowSummary','row-normalized','ColumnSummary','column-normalized');
cm.Title = 'Test Verisi İcin Es Olusum Matrisi';

Respuestas (2)

Yongjian Feng
Yongjian Feng el 3 de Dic. de 2021
What is confusion.getMatrix? The built-in confusion is a function. There is another confusionmat, but the return arguments don't match yours.

yanqi liu
yanqi liu el 27 de Dic. de 2021
yes,sir,may be use
[c_matrix,Result,RefereceResult]= confusion(actual,predict_label);

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