How to index Neural Network for loop

I would like to run this loop 4 times for the InitialLearnRate values of 0.0001, 0.001, 0.01, and 0.1. I would like to index the loop as well so I can compare the fracCorrect for each loop. Thank you!

InitialLearnRate = [0.0001,0.001,0.01,0.1]

augmentedDS_test = zeros(1,length(InitialLearnRate))

predictions = zeros(1,length(InitialLearnRate))

fracCorrect = zeros(1,length(InitialLearnRate))

for i = InitialLearnRate

imageDS = imageDatastore('deeplearning_course_files','IncludeSubfolders',true,'LabelSource','foldernames');

[wormTrain,wormTest] = splitEachLabel(imageDS,0.2); % takes x images from

augmentedDS_train = augmentedImageDatastore([227 227],wormTrain,'ColorPreprocessing','gray2rgb')

augmentedDS_test = augmentedImageDatastore([227 227],wormTest,'ColorPreprocessing','gray2rgb')

net = alexnet;

layers = net.Layers

fc = fullyConnectedLayer(2);

layers(end-2) = fc;

layers(end) = classificationLayer;

options = trainingOptions('sgdm','InitialLearnRate',i,'Momentum',0.1,'MaxEpochs',15)

[wormnet,info] = trainNetwork(augmentedDS_train,layers,options);

predictions = classify(wormnet,augmentedDS_test);

wormActual = wormTest.Labels;

numCorrect = nnz(predictions == wormActual);

fracCorrect = numCorrect/numel(predictions)

end

confusionchart(wormTest.Labels,predictions)

plot(info.TrainingLoss)

Answer 1

[Anshika Chaurasia]

You can consider trying indexing as given below:

for i = 1:length(InitialLearnRate)
....
options = trainingOptions('sgdm','InitialLearnRate',InitialLearnRate(i),'Momentum',0.1,'MaxEpochs',15)
....
fracCorrect(i) = numCorrect/numel(predictions)
...
end

[Justin Hayes]

Thank you very much!