PrincipalComponentAnalysis

Extract most variance of data set using Principal Component Analysis procedure.

	PCA - Performs the PCA on provided data, create the feature vector and normalization coefficients (mean and standard deviation of variables)
	ApplyPCATransformation - Applies previously obtained PCA transformation coefficients to new data.
	ReversePCATransformation - Reverses PCA process. Can be used to transform data back to original feature space.