75 #ifndef ROOT_TMVA_MethodCFMlpANN
76 #define ROOT_TMVA_MethodCFMlpANN
88 #ifndef ROOT_TMVA_MethodBase
91 #ifndef ROOT_TMVA_MethodCFMlpANN_Utils
107 const TString& theOption =
"3000:N-1:N-2",
void Train(void)
training of the Clement-Ferrand NN classifier
void DeclareOptions()
define the options (their key words) that can be set in the option string know options: NCycles=xx :t...
void NN_ava(Double_t *)
auxiliary functions
void ReadWeightsFromXML(void *wghtnode)
read weights from xml file
Int_t GetClass(Int_t ivar) const
static MethodCFMlpANN * fgThis
Int_t DataInterface(Double_t *, Double_t *, Int_t *, Int_t *, Int_t *, Int_t *, Double_t *, Int_t *, Int_t *)
data interface function
virtual ~MethodCFMlpANN(void)
destructor
#define ClassDef(name, id)
std::vector< Int_t > * fClass
virtual Bool_t HasAnalysisType(Types::EAnalysisType type, UInt_t numberClasses, UInt_t)
CFMlpANN can handle classification with 2 classes.
const Ranking * CreateRanking()
Double_t GetMvaValue(Double_t *err=0, Double_t *errUpper=0)
returns CFMlpANN output (normalised within [0,1])
MethodCFMlpANN(const TString &jobName, const TString &methodTitle, DataSetInfo &theData, const TString &theOption="3000:N-1:N-2", TDirectory *theTargetDir=0)
standard constructor option string: "n_training_cycles:n_hidden_layers" default is: n_training_cycles...
void MakeClassSpecificHeader(std::ostream &, const TString &="") const
write specific classifier response for header
void AddWeightsXMLTo(void *parent) const
write weights to xml file
Double_t EvalANN(std::vector< Double_t > &, Bool_t &isOK)
evaluates NN value as function of input variables
void GetHelpMessage() const
get help message text
void ReadWeightsFromStream(std::istream &istr)
read back the weight from the training from file (stream)
Double_t NN_fonc(Int_t, Double_t) const
activation function
Describe directory structure in memory.
void Init(void)
default initialisation called by all constructors
void ProcessOptions()
decode the options in the option string
Abstract ClassifierFactory template that handles arbitrary types.
void MakeClassSpecific(std::ostream &, const TString &) const
void PrintWeights(std::ostream &o) const
write the weights of the neural net
virtual void ReadWeightsFromStream(std::istream &)=0
static MethodCFMlpANN * This(void)
static pointer to this object (required for external functions
Double_t GetData(Int_t isel, Int_t ivar) const