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#ifndef EGAMMAOBJECTS_GBRTreeD
#define EGAMMAOBJECTS_GBRTreeD
//////////////////////////////////////////////////////////////////////////
// //
// GBRForest //
// //
// A fast minimal implementation of Gradient-Boosted Regression Trees //
// which has been especially optimized for size on disk and in memory. //
// //
// Designed to be built from TMVA-trained trees, but could also be //
// generalized to otherwise-trained trees, classification, //
// or other boosting methods in the future //
// //
// Josh Bendavid - CERN //
//////////////////////////////////////////////////////////////////////////
// The decision tree is implemented here as a set of two arrays, one for
// intermediate nodes, containing the variable index and cut value, as well
// as the indices of the 'left' and 'right' daughter nodes. Positive indices
// indicate further intermediate nodes, whereas negative indices indicate
// terminal nodes, which are stored simply as a vector of regression responses
#include "CondFormats/Serialization/interface/Serializable.h"
#include <vector>
class GBRTreeD {
public:
GBRTreeD() {}
template <typename InputTreeT>
GBRTreeD(const InputTreeT &tree);
//double GetResponse(const float* vector) const;
double GetResponse(int termidx) const { return fResponses[termidx]; }
int TerminalIndex(const float *vector) const;
std::vector<double> &Responses() { return fResponses; }
const std::vector<double> &Responses() const { return fResponses; }
std::vector<unsigned short> &CutIndices() { return fCutIndices; }
const std::vector<unsigned short> &CutIndices() const { return fCutIndices; }
std::vector<float> &CutVals() { return fCutVals; }
const std::vector<float> &CutVals() const { return fCutVals; }
std::vector<int> &LeftIndices() { return fLeftIndices; }
const std::vector<int> &LeftIndices() const { return fLeftIndices; }
std::vector<int> &RightIndices() { return fRightIndices; }
const std::vector<int> &RightIndices() const { return fRightIndices; }
protected:
std::vector<unsigned short> fCutIndices;
std::vector<float> fCutVals;
std::vector<int> fLeftIndices;
std::vector<int> fRightIndices;
std::vector<double> fResponses;
COND_SERIALIZABLE;
};
//_______________________________________________________________________
inline int GBRTreeD::TerminalIndex(const float *vector) const {
int index = 0;
unsigned short cutindex = fCutIndices[0];
float cutval = fCutVals[0];
while (true) {
if (vector[cutindex] > cutval) {
index = fRightIndices[index];
} else {
index = fLeftIndices[index];
}
if (index > 0) {
cutindex = fCutIndices[index];
cutval = fCutVals[index];
} else {
return (-index);
}
}
}
//_______________________________________________________________________
template <typename InputTreeT>
GBRTreeD::GBRTreeD(const InputTreeT &tree)
: fCutIndices(tree.CutIndices()),
fCutVals(tree.CutVals()),
fLeftIndices(tree.LeftIndices()),
fRightIndices(tree.RightIndices()),
fResponses(tree.Responses()) {}
#endif
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