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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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