Question
I used the neural network toolbox ( nprtool ) for classifying my objects. i used 75% of data for training and 15% for both validation and testing.also i considered 50 neurons for hidden layers. the progress stops because of validation checks (at 6). how can i improve the performance of this network? i couldn't find out how to change validation check or gradient ,....if you have any suggestion i will be very appreciate to hear that.
Expert Answer
John Michell
PhD Expert
Answered Aug 24, 2026
Insufficient information
Which of the MATLAB classification example datasets are you using? help nndatasets doc nndatasets Number of classes c =? Input vector dimensionality I = 1 Number of examples N = ? [ I N ] = size(input) [ O N ] = size(target)% O = c Default 70/15/15 data division? (75/15/15 doesn't add to 100)
Some problems require multiple(e.g., 10) designs for every value of hidden nodes that are tried.
For example, search the NEWSGROUP and ANSWERS using
greg patternnet Ntrials Sorry I can't give you much advice on how to optimize the use of nprtool. However, consulting my command line code should be more than worthwhile.
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