Question
I need a workable Back Propagation NN code. My Inputs are 100X3 dimension and outputs are 100X2 dimension.Sample size is 100. For example 1st 5 samples are inputs [-46 -69 -82; -46 -69 -82; -46 -69 -82; -46 -69 -82; -46 -69 -82;... ] and outputs are [0 0;2 1;5 5;4 3; 3 5;...]. Please suggest me if BP is suitable for my problem and what learning technique and activation function will be better to solve this problem? Do I need to apply generalization? Kindly help me with the matlab code if possible. Thank you very much.
Expert Answer
Kshitij Singh
PhD Expert
Answered Aug 16, 2026
Convert to matrices and transpose
[I N ] = size(inputs) [ O N ] = size(targets)
Use fitnet for regression and curve-fitting
help fitnet doc fitnet
Use patternnet for classification and pattern-recognition
For examples beyond the help/doc documentation try searching with
greg fitnet greg patternnet
in both the NEWSGROUP and ANSWERS.
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