Wavelet Packet Decomposition, Feature Selection and SVM
===

I want to know more about a fault detection model using Wavelet Packet Decomposition, Feature Selection and SVM. One can read some related papers here:

http://ieeexplore.ieee.org/xpls/abs_all.jsp?arnumber=4547208

https://mospace.umsystem.edu/xmlui/bitstream/handle/10355/4845/research.pdf?sequence=3

My question is in "Feature Selection" step, that we need to choose Wavelet Packet Nodes (with their computed rms value) as feature for the final SVM classifier. In SVM we need to know also label of each vector (+1, -1) but how can we obtain this label during the feature selection process. I really don't understand so much about Genetic Algorithm (GA) using 10-folds SVM as in the above papers. Anyone can explain to me about this?  