setDir  = fullfile(toolboxdir('machine'),'machine data','imagesets');

imds = imageDatastore(setDir,'IncludeSubfolders',true,'LabelSource',...
    'foldernames');
[trainingSet,testSet] = splitEachLabel(imds,0.3,'randomize');
bag = bagOfFeatures(trainingSet);
categoryClassifier = trainImageCategoryClassifier(trainingSet,bag);
confMatrix = evaluate(categoryClassifier,testSet)
mean(diag(confMatrix))
img = imread(fullfile(setDir,'negative','e_images_3.jpg'));
[labelIdx, score] = predict(categoryClassifier,img);
categoryClassifier.Labels(labelIdx)