Hi all. My neural network is for printed text recognition. I used this dataset: https://archive.ics.uci.edu/ml/datasets/Letter+Recognition My question is: why when data is divided 70% for train, 15% for validation and 15% for test, all graphics are the same, and everytime ''validation check '' = 0 .Training continues until the maximum epochs. This is part from my code:
targets = full(ind2vec(letters)); %matrix 26x16000 targets
inputs = train_set.';% matrix 16x16000 inputs
net= patternnet(40,'traingd'); net.trainparam.epochs = 1300; net.performFcn = 'mse'; net.performParam.ratio = 0.5; net.trainParam.goal = 1e-2;net.trainParam.show = 1;net.trainParam.lr = 0.1; net.trainParam.max_fail = 5; % Choose Input and Output Pre/Post-Processing Functions
net.inputs{1}.processFcns = {'removeconstantrows','mapminmax'};net.outputs{2}.processFcns = {'removeconstantrows','mapminmax'}; % Setup Division of Data for Training, Validation, Testing
net.divideFcn = 'dividerand'; % Divide data randomly
net.divideMode = 'sample'; % Divide up every sample
net.divideParam.trainRatio = 70/100; net.divideParam.valRatio = 15/100; net.divideParam.testRatio = 15/100; net = train(net,inputs,targets) %test
outputs = net(inputs);errors = gsubtract(targets,outputs);%sim
sim_attribs = attribs(end-3999:end, :);check = sim_attribs.';
My second quest is: why graphic ''confusion'' don't work (she is blurred and nothing is visible) ?
Best Answer