How can I get a confusion matrix after I train my AI using DeepNetworkDesigner?

Run this script to create the network layers, import training and validation data, and train the network. The network layers are stored in the workspace variable layers. The trained network is stored in the workspace variable net.

To learn more, see Generate MATLAB Code From Deep Network Designer.

Auto-generated by MATLAB on 11-Apr-2022 19:53:23

Load Initial Parameters

Load parameters for network initialization. For transfer learning, the network initialization parameters are the parameters of the initial pretrained network.

trainingSetup = load("C:\Users\ph20aap\OneDrive - University of Hertfordshire\matlab_project_saves\faces_0001_64_gpu\faces_0001_64_gpu.mat");

Import Data

Import training and validation data.

imdsTrain = imageDatastore("C:\Users\ph20aap\OneDrive - University of Hertfordshire\Data sets\FACES\Faces","IncludeSubfolders",true,"LabelSource","foldernames");

[imdsTrain, imdsValidation] = splitEachLabel(imdsTrain,0.75,"randomized");

% Resize the images to match the network input layer.

augimdsTrain = augmentedImageDatastore([227 227 3],imdsTrain);

augimdsValidation = augmentedImageDatastore([227 227 3],imdsValidation);

Set Training Options

Specify options to use when training.

opts = trainingOptions("sgdm",...

"ExecutionEnvironment","gpu",...

"InitialLearnRate",0.0001,...

"MaxEpochs",50,...

"MiniBatchSize",64,...

"Shuffle","every-epoch",...

"ValidationFrequency",30,...

"Plots","training-progress",...

"ValidationData",augimdsValidation);

Create Array of Layers

layers = [

imageInputLayer([227 227 3],"Name","data","Mean",trainingSetup.data.Mean)

convolution2dLayer([11 11],96,"Name","conv1","BiasLearnRateFactor",2,"Stride",[4 4],"Bias",trainingSetup.conv1.Bias,"Weights",trainingSetup.conv1.Weights)

reluLayer("Name","relu1")

crossChannelNormalizationLayer(5,"Name","norm1","K",1)

maxPooling2dLayer([3 3],"Name","pool1","Stride",[2 2])

groupedConvolution2dLayer([5 5],128,2,"Name","conv2","BiasLearnRateFactor",2,"Padding",[2 2 2 2],"Bias",trainingSetup.conv2.Bias,"Weights",trainingSetup.conv2.Weights)

reluLayer("Name","relu2")

crossChannelNormalizationLayer(5,"Name","norm2","K",1)

maxPooling2dLayer([3 3],"Name","pool2","Stride",[2 2])

convolution2dLayer([3 3],384,"Name","conv3","BiasLearnRateFactor",2,"Padding",[1 1 1 1],"Bias",trainingSetup.conv3.Bias,"Weights",trainingSetup.conv3.Weights)

reluLayer("Name","relu3")

groupedConvolution2dLayer([3 3],192,2,"Name","conv4","BiasLearnRateFactor",2,"Padding",[1 1 1 1],"Bias",trainingSetup.conv4.Bias,"Weights",trainingSetup.conv4.Weights)

reluLayer("Name","relu4")

groupedConvolution2dLayer([3 3],128,2,"Name","conv5","BiasLearnRateFactor",2,"Padding",[1 1 1 1],"Bias",trainingSetup.conv5.Bias,"Weights",trainingSetup.conv5.Weights)

reluLayer("Name","relu5")

maxPooling2dLayer([3 3],"Name","pool5","Stride",[2 2])

fullyConnectedLayer(4096,"Name","fc6","BiasLearnRateFactor",2,"Bias",trainingSetup.fc6.Bias,"Weights",trainingSetup.fc6.Weights)

reluLayer("Name","relu6")

dropoutLayer(0.5,"Name","drop6")

fullyConnectedLayer(4096,"Name","fc7","BiasLearnRateFactor",2,"Bias",trainingSetup.fc7.Bias,"Weights",trainingSetup.fc7.Weights)

reluLayer("Name","relu7")

dropoutLayer(0.5,"Name","drop7")

fullyConnectedLayer(6,"Name","fc")

softmaxLayer("Name","prob")

classificationLayer("Name","classoutput")];

Train Network

Train the network using the specified options and training data.

[net, traininfo] = trainNetwork(augimdsTrain,layers,opts);

this is the script i genarated using DeepNetworkDesigner, I tried y=predict(net,augimdsValidation);

Unrecognized function or variable 'net'.

and it is giving me an error as I am new to matlab I am really struggiling to figure out the issue here.

Powel Hancy 2022-4-14

I am usining the matlab version R2021a as my university is not upgraded to the 2022 version so I will have to use the 2021a.... In 2021a there is only 2 options in export that is 1. Export to work space 2.Generate Live script. The genarated live script is the one I have posted above. Is there any other way to get the Confusion matrix from the Trained networks i have?

Powel Hancy 2022-4-18

As I could not solve the issue in DeepNetworkDesigner, I found a temperory solution, that is create the network using DND and export the code before training it, and copy paste the code in Experiment manager app and do the training there.. Experiment manage will produce confusion matrix for you.

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