/usr/include/root/TMVA/ExpectedErrorPruneTool.h is in libroot-tmva-dev 5.34.30-0ubuntu8.
This file is owned by root:root, with mode 0o644.
The actual contents of the file can be viewed below.
1 2 3 4 5 6 7 8 9 10 11 12 13 14 15 16 17 18 19 20 21 22 23 24 25 26 27 28 29 30 31 32 33 34 35 36 37 38 39 40 41 42 43 44 45 46 47 48 49 50 51 52 53 54 55 56 57 58 59 60 61 62 63 64 65 66 67 68 69 70 71 72 73 74 75 76 77 78 79 80 81 82 83 84 85 86 87 88 89 90 91 92 93 94 95 96 97 98 | /**********************************************************************************
* Project: TMVA - a Root-integrated toolkit for multivariate data analysis *
* Package: TMVA *
* Class : TMVA::DecisionTree *
* Web : http://tmva.sourceforge.net *
* *
* Description: *
* Implementation of a Decision Tree *
* *
* Authors (alphabetical): *
* Andreas Hoecker <Andreas.Hocker@cern.ch> - CERN, Switzerland *
* Helge Voss <Helge.Voss@cern.ch> - MPI-K Heidelberg, Germany *
* Kai Voss <Kai.Voss@cern.ch> - U. of Victoria, Canada *
* Doug Schouten <dschoute@sfu.ca> - Simon Fraser U., Canada *
* *
* Copyright (c) 2005: *
* CERN, Switzerland *
* U. of Victoria, Canada *
* MPI-K Heidelberg, Germany *
* *
* Redistribution and use in source and binary forms, with or without *
* modification, are permitted according to the terms listed in LICENSE *
* (http://mva.sourceforge.net/license.txt) *
* *
**********************************************************************************/
#ifndef ROOT_TMVA_ExpectedErrorPruneTool
#define ROOT_TMVA_ExpectedErrorPruneTool
/////////////////////////////////////////////////////////////////////////////////////////////////////////////
// ExpectedErrorPruneTool - a helper class to prune a decision tree using the expected error (C4.5) method //
// //
// Uses an upper limit on the error made by the classification done by each node. If the S/S+B of the node //
// is f, then according to the training sample, the error rate (fraction of misclassified events by this //
// node) is (1-f). Now f has a statistical error according to the binomial distribution hence the error on //
// f can be estimated (same error as the binomial error for efficency calculations //
// ( sigma = sqrt(eff(1-eff)/nEvts ) ) //
// //
// This tool prunes branches from a tree if the expected error of a node is less than that of the sum of //
// the error in its descendants. //
// //
/////////////////////////////////////////////////////////////////////////////////////////////////////////////
#include <vector>
#include <map>
#ifndef ROOT_TMath
#include "TMath.h"
#endif
#ifndef ROOT_TMVA_IPruneTool
#include "TMVA/IPruneTool.h"
#endif
namespace TMVA {
class MsgLogger;
class ExpectedErrorPruneTool : public IPruneTool {
public:
ExpectedErrorPruneTool( );
virtual ~ExpectedErrorPruneTool( );
// returns the PruningInfo object for a given tree and test sample
virtual PruningInfo* CalculatePruningInfo( DecisionTree* dt, const IPruneTool::EventSample* testEvents = NULL,
Bool_t isAutomatic = kFALSE );
public:
// set the increment dalpha with which to scan for the optimal prune strength
inline void SetPruneStrengthIncrement( Double_t dalpha ) { fDeltaPruneStrength = dalpha; }
private:
void FindListOfNodes( DecisionTreeNode* node );
Double_t GetNodeError( DecisionTreeNode* node ) const;
Double_t GetSubTreeError( DecisionTreeNode* node ) const;
Int_t CountNodes( DecisionTreeNode* node, Int_t icount = 0 );
Double_t fDeltaPruneStrength; //! the stepsize for optimizing the pruning strength parameter
Double_t fNodePurityLimit; //! the purity limit for labelling a terminal node as signal
std::vector<DecisionTreeNode*> fPruneSequence; //! the (optimal) prune sequence
// std::multimap<const Double_t, Double_t> fQualityMap; //! map of tree quality <=> prune strength
mutable MsgLogger* fLogger; // message logger
MsgLogger& Log() const { return *fLogger; }
};
inline Int_t ExpectedErrorPruneTool::CountNodes( DecisionTreeNode* node, Int_t icount ) {
DecisionTreeNode* l = (DecisionTreeNode*)node->GetLeft();
DecisionTreeNode* r = (DecisionTreeNode*)node->GetRight();
Int_t counter = icount + 1; // count this node
if(!(node->IsTerminal()) && l != NULL && r != NULL) {
counter = CountNodes(l,counter);
counter = CountNodes(r,counter);
}
return counter;
}
}
#endif
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