I would like to know which normalization method can be used to implement feature extraction (PCA) and provide it as an input to any classifier. The output of the PCA is not lying in the range 0-1. Should I normalize the data again before giving it as an input to the classifier? I am using Colon Tumor microarray data from Kentridge repository.
Poornima Nagaraj
PCA is a non-supervised method. it may be insufficient to classify your data. you can select a supervised classification method such as LDA, SVM, Random Forset, Boosting, Decision tree etc.
As for Normalization you can do Min-Max normalization to implement feature extraction (PCA) and provide it as an input to any classifier.
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