Prepare data for SVM, Is it valid to normalise the data before and after PCA dimension reduction
Depending on the language of your choice, you may or may not have to normalise the data yourself - for example the e1071 package in R does this automatically for you. As this is built off the 'libsvm' library, it might be that this is also the case there - the library documentation is your best source. As for the normalisation values, you should definitely use the same [min,max] values from the training set for the test set as well. Also, I would reccomend reducing the dimensionality of your data first, than normalising before running a svm. hth