class TMVA::VariablePCATransform: public TMVA::VariableTransformBase

 constructor

 destructor

 initialization of the transformation.
 Has to be called in the preparation and not in the constructor,
 since the number of classes it not known at construction, but
 only after the creation of the DataSet which might be later.

 calculate the principal components using the ROOT class TPrincipal
 and the normalization

 apply the principal component analysis

 apply the principal component analysis
 TODO: implementation of inverse transformation
    Log() << kFATAL << "Inverse transformation for PCA transformation not yet implemented. Hence, this transformation cannot be applied together with regression. Please contact the authors if necessary." << Endl;

 calculate the principal components for the signal and the background data
 it uses the MakePrincipal method of ROOT's TPrincipal class

 Calculate the principal components from the original data vector
 x, and return it in p (function extracted from TPrincipal::X2P)
 It's the users responsibility to make sure that both x and p are
 of the right size (i.e., memory must be allocated for p)

 Perform the back-transformation from the principal components
 pc, and return x
 It's the users responsibility to make sure that both x and pc are
 of the right size (i.e., memory must be allocated for p)

 write mean values to stream

 create XML description of PCA transformation

 Read the transformation matrices from the xml node

 Read mean values from input stream

 creates C++ code fragment of the PCA transform for inclusion in standalone C++ class