How to crete Input and Target data for Neural Network Training?
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Harsimrat Parmar
on 14 Mar 2015
Commented: Greg Heath
on 17 Mar 2015
I have character dataset for handwriting recognition from 110 users. Each user writes 110 different characters twice. So basically there are 110*110*2 images in total. I wrote a feature extraction code and now have 80 features per image (character). The FE code has created 110 text files representing each character i.e. one file represents one of the 110 characters from all the users. Each file has name of the user and image number followed by 80 features separated by comma. Since there are 110 characters to be recognized, I know there should be 110 classes but I am not sure how to create matrices for input and target so the dimensions match. Could someone please help me, how can solve this problem.
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Greg Heath
on 15 Mar 2015
N = 110*110*2 % 24200
[ I N ] = size(input) % [ 80 N ]
[ O N ] = size(target) % [ 110 N ] e.g, [ repmat(eye(110), 1, 220)]
Hope this helps.
Thank you for formally accepting my answer
Greg
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Greg Heath
on 17 Mar 2015
help vec2ind
doc vec2ind
help ind2vec2
doc ind2vec2
For examples search the NEWSGROUP and ANSWERS using
patternnet ind2vec vec2ind
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