What is the best classifier for train the handwritten characters?
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I am doing my project in OCR.I have tried feed forward back propagation , Perceptron etc for training .Finally use radial basis function and got more accuracy during training phase.But the problem arise during testing part.For training , i have taken 710 characters and got 97.58% performance.But during testing i have got poor results(got 5-20% accuracy). I have used image that are written by same person for testing and training phase. Now i don't know what to do... .My last option is to change my classifier. My project depends on these. I have searched online and tried for several days(nearly 1 month) to find a solution, but nothing has worked.Could anybody help me please..............
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Accepted Answer
Greg Heath
on 14 May 2013
help patternnet
Make sure your target matrix contains columns of the unit matrix eye(c) where c is the number of classes.
Search for examples in NEWSGROUP and ANSWERS using
patternnet
Hope this helps.
Greg
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Greg Heath
on 16 May 2013
However, even if your code is perfect, you cannot be successful without a good set of features. I can check your code, but you will have to refer to one of the resident image gurus w.r.t. features.
More Answers (1)
Walter Roberson
on 14 May 2013
No-one knows what the "best" classifier is. We expect that a better one will be invented within the next 50,000 years. In the meantime the best of the known classifiers very likely has performance depending on the kind of characters being analyzed. So far, no-one has found any that can read what Nature has writ in the frost on the windows.
2 Comments
Jan
on 16 May 2013
Edited: Jan
on 16 May 2013
@Minu: Reading hand-written characters is a serious problem. Note that pupils require years to learn this, although their visual system has been optimized for millions of years (and this is an understatement).
There cannot be a "best" method, because it will depend on the age and nationality of the writers, on the fact if they care for readability as on bank cheques, on the properties of the paper and on the quality of the camera, e.g. number of gray shades.
In consequence I assume, that even after years of further investigations, you will not find a "best" method, but a bunch of almost satisfying solutions.
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