class TMVA::MethodFDA: public TMVA::MethodBase, public TMVA::IFitterTarget

 standard constructor

 constructor from weight file

 default initialisation

 define the options (their key words) that can be set in the option string

 format of function string:
    "x0*(0)+((1)/x1)**(2)..."
 where "[i]" are the parameters, and "xi" the input variables

 format of parameter string:
    "(-1.2,3.4);(-2.3,4.55);..."
 where the numbers in "(a,b)" correspond to the a=min, b=max parameter ranges;
 each parameter defined in the function string must have a corresponding range

 translate formula string into TFormula, and parameter string into par ranges

 the option string is decoded, for availabel options see "DeclareOptions"

 destructor

 FDA can handle classification with 2 classes and regression with one regression-target

 delete and clear all class members

 FDA training

 display fit parameters
 check maximum length of variable name

 compute estimator for given parameter set (to be minimised)
   const Double_t sumOfWeights[]                = { fSumOfWeightsSig, fSumOfWeightsBkg, fSumOfWeights };

 formula interpretation

 returns MVA value for given event

 write the weight from the training to a file (stream)

 read back the training results from a file (stream)

 create XML description for LD classification and regression
 (for arbitrary number of output classes/targets)

 read coefficients from xml weight file

 write FDA-specific classifier response

 get help message text

 typical length of text line:
         "|--------------------------------------------------------------|"

 ranking of input variables

 no check of options at this place