need to plot the accuracy vs epoch graph

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allImages = imageDatastore('TrainingData', 'IncludeSubfolders', true,...
'LabelSource', 'foldernames');
%% Split data into training and test sets
[trainingImages, testImages] = splitEachLabel(allImages, 0.8, 'randomize');
%% Load Pre-trained Network (AlexNet)
% AlexNet is a pre-trained network trained on 1000 object categories.
% AlexNet is avaliable as a support package on FileExchange.
alex = alexnet;
%% Review Network Architecture
layers = alex.Layers
%% Modify Pre-trained Network
% AlexNet was trained to recognize 1000 classes, we need to modify it to
% recognize just 4 classes.
layers(23) = fullyConnectedLayer(4); % change this based on # of classes
layers(25) = classificationLayer
%% Perform Transfer Learning
% For transfer learning we want to change the weights of the network ever so slightly. How
% much a network is changed during training is controlled by the learning
% rates.
opts = trainingOptions('sgdm', 'InitialLearnRate', 0.001,...
'MaxEpochs', 5, 'MiniBatchSize', 16);
%% Set custom read function
% One of the great things about imageDataStore it lets you specify a
% "custom" read function, in this case it is simply resizing the input
% images to 227x227 pixels which is what AlexNet expects. You can do this by
% specifying a function handle of a function with code to read and
% pre-process the image.
trainingImages.ReadFcn = @readFunctionTrain;
%% Train the Network
% This process usually takes about 5-20 minutes on a desktop GPU.
myNet = trainNetwork(trainingImages, layers, opts);
%% Test Network Performance
% Now let's the test the performance of our new "snack recognizer" on the test set.
testImages.ReadFcn = @readFunctionTrain;
predictedLabels = classify(myNet, testImages);
accuracy = mean(predictedLabels == testImages.Labels)
confusionchart(predictedLabels, testImages.Labels)
Hello, for the code above, I need to plot the accuracy vs epoch graph. How can I do that? Thank you!

回答(1 个)

Joss Knight
Joss Knight 2022-11-14
Add Plots="training-progress" to your training options.
FWIW, you shouldn't use ReadFcn for resizing images, it dramatically slows down file access. Use augmentedImageDatastore instead.

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