How to get validation test and training errors of a neural network?
Learn how to get validation, test, and training errors for your neural network in MATLAB. Improve your models performance & prevent overfitting! Read more now.
Learn how to get validation, test, and training errors for your neural network in MATLAB. Improve your models performance & prevent overfitting! Read more now.
BOTH documentation commands
help patternnet and doc patternnet
have the following sample code for CLASSIFICATION & PATTERN-RECOGNITION:
[x,t] = iris_dataset; net = patternnet(10); net = train(net,x,t); view(net) y = net(x); perf = perform(net,t,y); classes = vec2ind(y);
However, the following are missing
1. Dimensions of x and t 2. Plots of x, t, and t vs x 3. Minimum possible number of hidden nodes 4. Initial state of the RNG (Needed for duplication) 5. Training record, tr 6. Plots of e = y-t vs x 7. Misclassified cases 8. trn/val/tst Error rates
For details see my NEWSGROUP posts
SIZES OF MATLAB CLASSIFICATION EXAMPLE DATA SETS http://www.mathworks.com/matlabcentral/newsreader/... view_thread/339984 and BEYOND THE HELP/DOC DOCUMENTATION : PATTERNNET for NN Classification and PatternRecognition http://www.mathworks.com/matlabcentral/newsreader/... view_thread/344832
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