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Reference Guide
MethodRSNNS.h
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1// @(#)root/tmva/rmva $Id$
2// Author: Omar Zapata,Lorenzo Moneta, Sergei Gleyzer 2015
3
4/**********************************************************************************
5 * Project: TMVA - a Root-integrated toolkit for multivariate data analysis *
6 * Package: TMVA *
7 * Class : RMethodRSNNS *
8 * *
9 * Description: *
10 * R´s Package RSNNS method based on ROOTR *
11 * *
12 **********************************************************************************/
13
14#ifndef ROOT_TMVA_RMethodRSNNS
15#define ROOT_TMVA_RMethodRSNNS
16
17//////////////////////////////////////////////////////////////////////////
18// //
19// RMethodRSNNS //
20// //
21// //
22//////////////////////////////////////////////////////////////////////////
23
24#include "TMVA/RMethodBase.h"
25
26namespace TMVA {
27
28 class Factory; // DSMTEST
29 class Reader; // DSMTEST
30 class DataSetManager; // DSMTEST
31 class Types;
32 class MethodRSNNS : public RMethodBase {
33
34 public :
35
36 // constructors
37 MethodRSNNS(const TString &jobName,
38 const TString &methodTitle,
39 DataSetInfo &theData,
40 const TString &theOption = "");
41
43 const TString &theWeightFile);
44
45
46 ~MethodRSNNS(void);
47 void Train();
48 // options treatment
49 void Init();
50 void DeclareOptions();
51 void ProcessOptions();
52 // create ranking
54 {
55 return NULL; // = 0;
56 }
57
58
59 Bool_t HasAnalysisType(Types::EAnalysisType type, UInt_t numberClasses, UInt_t numberTargets);
60
61 // performs classifier testing
62 virtual void TestClassification();
63
64
65 Double_t GetMvaValue(Double_t *errLower = 0, Double_t *errUpper = 0);
66
68 // the actual "weights"
69 virtual void AddWeightsXMLTo(void * /*parent*/) const {} // = 0;
70 virtual void ReadWeightsFromXML(void * /*wghtnode*/) {} // = 0;
71 virtual void ReadWeightsFromStream(std::istream &) {} //= 0; // backward compatibility
72
73 void ReadModelFromFile();
74
75 // signal/background classification response for all current set of data
76 virtual std::vector<Double_t> GetMvaValues(Long64_t firstEvt = 0, Long64_t lastEvt = -1, Bool_t logProgress = false);
77
78 private :
80 friend class Factory; // DSMTEST
81 friend class Reader; // DSMTEST
82 protected:
84 std::vector<Float_t> fProbResultForTrainSig;
85 std::vector<Float_t> fProbResultForTestSig;
86
87 TString fNetType;//default RMPL
88 //RSNNS Options for all NN methods
89 TString fSize;//number of units in the hidden layer(s)
90 UInt_t fMaxit;//maximum of iterations to learn
91
92 TString fInitFunc;//the initialization function to use
93 TString fInitFuncParams;//the parameters for the initialization function (type 6 see getSnnsRFunctionTable() in RSNNS package)
94
95 TString fLearnFunc;//the learning function to use
96 TString fLearnFuncParams;//the parameters for the learning function
97
98 TString fUpdateFunc;//the update function to use
99 TString fUpdateFuncParams;//the parameters for the update function
100
101 TString fHiddenActFunc;//the activation function of all hidden units
102 Bool_t fShufflePatterns;//should the patterns be shuffled?
103 Bool_t fLinOut;//sets the activation function of the output units to linear or logistic
104
105 TString fPruneFunc;//the pruning function to use
106 TString fPruneFuncParams;//the parameters for the pruning function. Unlike the
107 //other functions, these have to be given in a named list. See
108 //the pruning demos for further explanation.
109 std::vector<UInt_t> fFactorNumeric; //factors creations
110 //RSNNS mlp require a numeric factor then background=0 signal=1 from fFactorTrain
116 // get help message text
117 void GetHelpMessage() const;
118
120 };
121} // namespace TMVA
122#endif
unsigned int UInt_t
Definition: RtypesCore.h:42
bool Bool_t
Definition: RtypesCore.h:59
double Double_t
Definition: RtypesCore.h:55
long long Long64_t
Definition: RtypesCore.h:69
#define ClassDef(name, id)
Definition: Rtypes.h:324
int type
Definition: TGX11.cxx:120
This is a class to pass functions from ROOT to R.
This is a class to get ROOT's objects from R's objects.
Definition: TRObject.h:71
Class that contains all the data information.
Definition: DataSetInfo.h:60
Class that contains all the data information.
This is the main MVA steering class.
Definition: Factory.h:81
virtual void ReadWeightsFromStream(std::istream &)=0
static Bool_t IsModuleLoaded
Definition: MethodRSNNS.h:111
virtual void ReadWeightsFromStream(std::istream &)
Definition: MethodRSNNS.h:71
virtual void AddWeightsXMLTo(void *) const
Definition: MethodRSNNS.h:69
std::vector< Float_t > fProbResultForTrainSig
Definition: MethodRSNNS.h:84
ROOT::R::TRFunctionImport asfactor
Definition: MethodRSNNS.h:114
Bool_t fShufflePatterns
Definition: MethodRSNNS.h:102
TString fLearnFunc
Definition: MethodRSNNS.h:95
void GetHelpMessage() const
Double_t GetMvaValue(Double_t *errLower=0, Double_t *errUpper=0)
DataSetManager * fDataSetManager
Definition: MethodRSNNS.h:79
const Ranking * CreateRanking()
Definition: MethodRSNNS.h:53
Bool_t HasAnalysisType(Types::EAnalysisType type, UInt_t numberClasses, UInt_t numberTargets)
ROOT::R::TRFunctionImport predict
Definition: MethodRSNNS.h:112
TString fHiddenActFunc
Definition: MethodRSNNS.h:101
virtual std::vector< Double_t > GetMvaValues(Long64_t firstEvt=0, Long64_t lastEvt=-1, Bool_t logProgress=false)
get all the MVA values for the events of the current Data type
TString fUpdateFunc
Definition: MethodRSNNS.h:98
TString fUpdateFuncParams
Definition: MethodRSNNS.h:99
TString fLearnFuncParams
Definition: MethodRSNNS.h:96
virtual void TestClassification()
initialization
TString fPruneFuncParams
Definition: MethodRSNNS.h:106
MethodRSNNS(const TString &jobName, const TString &methodTitle, DataSetInfo &theData, const TString &theOption="")
Definition: MethodRSNNS.cxx:51
virtual void ReadWeightsFromXML(void *)
Definition: MethodRSNNS.h:70
TString fInitFuncParams
Definition: MethodRSNNS.h:93
std::vector< UInt_t > fFactorNumeric
Definition: MethodRSNNS.h:109
ROOT::R::TRFunctionImport mlp
Definition: MethodRSNNS.h:113
ROOT::R::TRObject * fModel
Definition: MethodRSNNS.h:115
std::vector< Float_t > fProbResultForTestSig
Definition: MethodRSNNS.h:85
Ranking for variables in method (implementation)
Definition: Ranking.h:48
The Reader class serves to use the MVAs in a specific analysis context.
Definition: Reader.h:63
EAnalysisType
Definition: Types.h:127
Basic string class.
Definition: TString.h:131
Abstract ClassifierFactory template that handles arbitrary types.