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Hi I know why feature scaling is preferred in SVM, I have two questions: 1-does anyone know of legit articles of books explaining it. I am writing my thesis and I need references. It doesnt have to be for SVM specific, even if it is for Neural Networks or other supervised learning algorithms it will be appreciated.

2-Other than the referencing part does anyone have another source for more explanations on the scaling or rescaling of inputs.

Thanks

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You can find this in "Elements of Statistical Learning" (http://web.stanford.edu/~hastie/local.ftp/Springer/OLD/ESLII_print4.pdf) on page 398. This is for neural nets.

Also, this is a very nice article that you can look at for more info on implementation (http://www.faqs.org/faqs/ai-faq/neural-nets/part2/section-16.html)

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  • $\begingroup$ Hi thank you that is a great reference. :-) Do you know of other sources that would go into detail about how to go about scaling and rescaling? $\endgroup$ – Kate Jul 18 '14 at 18:54
  • $\begingroup$ Just added it into the answer, HTH. $\endgroup$ – mike1886 Jul 18 '14 at 19:03
  • $\begingroup$ THANK YOU!!!! This is exactly the kind of thing I was looking for! :-) Cheers $\endgroup$ – Kate Jul 18 '14 at 19:10

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