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can somebody help me to generate a confusion matrix for this multisvm code?

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I have been trying to plot a confusion matrix for this svm code but im reaching nowhere,so the purpose of my code is to classify my 95 images into 3 classes, i have made the training_label which is the label of every image.then i don't know how to generate the confusion matrix. here is the code
close all
clear all
clc
srcFiles = dir('E:\sense\cata2\cata\all\*.jpg');
for i = 1 : length(srcFiles)
filename = strcat('E:\sense\cata2\cata\all\',srcFiles(i).name);
Img = imread(filename);
Img = imresize(Img,[256,256]);
%figure, imshow(Img); title('Image');
% Enhance Contrast
I = imadjust(Img,stretchlim(Img));
figure, imshow(I);title('Contrast Enhanced');
% Extract Features from query image
[Feature_Vector] = Extract_FeaturesofSoilforall(I);
whos Feature_Vector
% Load Training Features
[X,T] = cataractdataset;
TrainFeat = X;
Train_Label = T;
test = Feature_Vector;
result = multisvm(TrainFeat,Train_Label,test)
disp(result)
if result == 1
helpdlg(' grade1');
disp(' grade1 ');
elseif result == 2
helpdlg(' last ');
disp('last');
elseif result == 3
helpdlg('normal');
disp(' normal ');
end
confMat = confusionmat(,test )
end

Accepted Answer

Hadeer tawfik
Hadeer tawfik on 23 Oct 2016
confMat = confusionmat(Train_Label, results)
  2 Comments
Hadeer tawfik
Hadeer tawfik on 23 Oct 2016
Edited: Hadeer tawfik on 23 Oct 2016
This worked for me hince: results is a vector that contains the classifier results.
kokeb Dese
kokeb Dese on 9 Aug 2018
This is very interesting, but what if it is for all testing data confusion matrix together.

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