How to plot the confusion matrix of more than 2 classes?

clc
clear

% Load Image dataset
faceDatabase = imageSet('facedatabaseatt','recursive');

%splitting into training and testing sets

[training,test] = partition(faceDatabase,[0.8 0.2]);

% Extract HOG Features for training set 
featureCount = 1;
for i=1:size(training,2)
    for j = 1:training(i).Count
        trainingFeatures(featureCount,:) = extractHOGFeatures(read(training(i),j));
       % imshow(read(training(i),j));
        %pause(0.0011);
        trainingLabel{featureCount} = training(i).Description;    
        featureCount = featureCount + 1;
    end
    personIndex{i} = training(i).Description;
end

% Create 40 class classifier
faceClassifier = fitcknn(trainingFeatures,trainingLabel);

%testing
kk=1;
for person=1:40
    for j = 1:test(person).Count
        queryImage = read(test(person),j);
        queryFeatures = extractHOGFeatures(queryImage);
        actualLabel = predict(faceClassifier,queryFeatures);
        actualLabel=char(actualLabel);
        predictedLabel=test(person).Description;
        
        
        al(kk)=str2num(actualLabel(2:length(actualLabel)))
        pl(kk)=str2num(predictedLabel(2:length(predictedLabel))) 
        kk=kk+1;
       % Map back to training set to find identity
        %booleanIndex = strcmp(actualLabel, personIndex);
        %integerIndex = find(booleanIndex);

    end    
end
if isempty(al)==0
    accuracy=length(find(pl==al))/size(test,1)
end

[Bhaskar R]

This link can help you

https://in.mathworks.com/help/deeplearning/ref/plotconfusion.html