Utils/src/GBRForest.cxx



#include "../interface/GBRForest.h"
//#include <iostream>
#include "TMVA/DecisionTree.h"
#include "TMVA/MethodBDT.h"


ClassImp(GBRForest)


//_______________________________________________________________________
GBRForest::GBRForest() : 
  fInitialResponse(0.)
{

}

//_______________________________________________________________________
GBRForest::~GBRForest() 
{
  for (UInt_t i=0; i<fTrees.size(); ++i) {
    delete fTrees.at(i);
  }
}

//_______________________________________________________________________
GBRForest::GBRForest(const TMVA::MethodBDT *bdt) : 
  TNamed("GBRForest","GBRForest"),
  fInitialResponse(bdt->GetBoostWeights().front())
{
  
  const std::vector<TMVA::DecisionTree*> &forest = bdt->GetForest();
  for (std::vector<TMVA::DecisionTree*>::const_iterator it=forest.begin(); it!=forest.end(); ++it) {
    GBRTree *tree = new GBRTree(*it);
    fTrees.push_back(tree);
  }
}


Revision:	1.1
Committed:	Wed Sep 28 00:08:48 2011 UTC (13 years, 7 months ago) by bendavid
Content type:	text/plain
Branch:	MAIN
CVS Tags:	Mit_025e, Mit_025d, Mit_025c, Mit_025b, Mit_025a, Mit_025, Mit_025pre2
Log Message:	optimized bdt implementation for regression, so that disk and memory requirements are manageable
#	User	Rev	Content
1	bendavid	1.1
2
3
4			#include "../interface/GBRForest.h"
5			//#include <iostream>
6			#include "TMVA/DecisionTree.h"
7			#include "TMVA/MethodBDT.h"
8
9
10			ClassImp(GBRForest)
11
12
13			//_______________________________________________________________________
14			GBRForest::GBRForest() :
15			fInitialResponse(0.)
16			{
17
18			}
19
20			//_______________________________________________________________________
21			GBRForest::~GBRForest()
22			{
23			for (UInt_t i=0; i<fTrees.size(); ++i) {
24			delete fTrees.at(i);
25			}
26			}
27
28			//_______________________________________________________________________
29			GBRForest::GBRForest(const TMVA::MethodBDT *bdt) :
30			TNamed("GBRForest","GBRForest"),
31			fInitialResponse(bdt->GetBoostWeights().front())
32			{
33
34			const std::vector<TMVA::DecisionTree*> &forest = bdt->GetForest();
35			for (std::vector<TMVA::DecisionTree*>::const_iterator it=forest.begin(); it!=forest.end(); ++it) {
36			GBRTree tree = new GBRTree(it);
37			fTrees.push_back(tree);
38			}
39			}
40
41
42