Options for the FANN MVA method.
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#include <FastBDT.h>
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virtual void | load (const boost::property_tree::ptree &pt) override |
| Load mechanism to load Options from a xml tree. More...
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virtual void | save (boost::property_tree::ptree &pt) const override |
| Save mechanism to store Options in a xml tree. More...
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virtual po::options_description | getDescription () override |
| Returns a program options description for all available options.
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virtual std::string | getMethod () const override |
| Return method name.
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unsigned int | m_nTrees = 200 |
| Number of trees.
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unsigned int | m_nCuts = 8 |
| Number of cut Levels = log_2(Number of Cuts)
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unsigned int | m_nLevels = 3 |
| Depth of tree.
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double | m_shrinkage = 0.1 |
| Shrinkage during the boosting step.
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double | m_randRatio = 0.5 |
| Fraction of data to use in the stochastic training.
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Options for the FANN MVA method.
Definition at line 53 of file FastBDT.h.
◆ load()
void load |
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const boost::property_tree::ptree & |
pt | ) |
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overridevirtual |
Load mechanism to load Options from a xml tree.
- Parameters
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Implements Options.
Definition at line 53 of file FastBDT.cc.
55 int version = pt.get<
int>(
"FastBDT_version");
56 #if FastBDT_VERSION_MAJOR >= 5
57 if (version != 1 and version != 2) {
58 B2ERROR(
"Unknown weightfile version " << std::to_string(version));
59 throw std::runtime_error(
"Unknown weightfile version " + std::to_string(version));
63 B2ERROR(
"Unknown weightfile version " << std::to_string(version));
64 throw std::runtime_error(
"Unknown weightfile version " + std::to_string(version));
67 m_nTrees = pt.get<
int>(
"FastBDT_nTrees");
68 m_nCuts = pt.get<
int>(
"FastBDT_nCuts");
69 m_nLevels = pt.get<
int>(
"FastBDT_nLevels");
73 #if FastBDT_VERSION_MAJOR >= 5
76 m_flatnessLoss = pt.get<
double>(
"FastBDT_flatnessLoss");
77 m_sPlot = pt.get<
bool>(
"FastBDT_sPlot");
79 unsigned int numberOfIndividualNCuts = pt.get<
unsigned int>(
"FastBDT_number_individual_nCuts", 0);
80 m_individual_nCuts.resize(numberOfIndividualNCuts);
81 for (
unsigned int i = 0; i < numberOfIndividualNCuts; ++i) {
82 m_individual_nCuts[i] = pt.get<
unsigned int>(std::string(
"FastBDT_individual_nCuts") + std::to_string(i));
85 m_purityTransformation = pt.get<
bool>(
"FastBDT_purityTransformation");
86 unsigned int numberOfIndividualPurityTransformation = pt.get<
unsigned int>(
"FastBDT_number_individualPurityTransformation", 0);
87 m_individualPurityTransformation.resize(numberOfIndividualPurityTransformation);
88 for (
unsigned int i = 0; i < numberOfIndividualPurityTransformation; ++i) {
89 m_individualPurityTransformation[i] = pt.get<
bool>(std::string(
"FastBDT_individualPurityTransformation") + std::to_string(i));
93 m_flatnessLoss = -1.0;
double m_randRatio
Fraction of data to use in the stochastic training.
double m_shrinkage
Shrinkage during the boosting step.
unsigned int m_nLevels
Depth of tree.
unsigned int m_nCuts
Number of cut Levels = log_2(Number of Cuts)
unsigned int m_nTrees
Number of trees.
◆ save()
void save |
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boost::property_tree::ptree & |
pt | ) |
const |
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overridevirtual |
The documentation for this class was generated from the following files: