why my classification results are not correct

net = googlenet;
inputSize = net.Layers(1).InputSize
classNames = net.Layers(end).ClassNames;
numClasses = numel(classNames);
disp(classNames(randperm(numClasses,10)))
im = imread("D:\cotton\dataset\Alternaria fliph\(9).jpeg");
figure
imshow(im)
size(im)
im = imresize(im,inputSize(1:2));
figure
imshow(im)
[label,scores] = classify(net,im);
label
figure
imshow(im)
title(string(label) + ", " + num2str(100*scores(classNames == label),3) + "%");
[~,idx] = sort(scores,'descend');
idx = idx(5:-1:1);
classNamesTop = net.Layers(end).ClassNames(idx);
scoresTop = scores(idx);

figure
barh(scoresTop)
xlim([0 1])
title('Top 5 Predictions')
xlabel('')
yticklabels(classNamesTop)

Answer 1

[Image Analyst]

It was probably not trained with enough examples of the class it's getting wrong.