decision_forest_trainer.hpp
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#pragma once
template <class FeatureType,
class DataSet,
class LabelType,
class ExampleIndex,
class NodeType>
pcl::DecisionForestTrainer<FeatureType, DataSet, LabelType, ExampleIndex, NodeType>::
DecisionForestTrainer()
: num_of_trees_to_train_(1), decision_tree_trainer_()
{}
template <class FeatureType,
class DataSet,
class LabelType,
class ExampleIndex,
class NodeType>
pcl::DecisionForestTrainer<FeatureType, DataSet, LabelType, ExampleIndex, NodeType>::
~DecisionForestTrainer()
{}
template <class FeatureType,
class DataSet,
class LabelType,
class ExampleIndex,
class NodeType>
void
pcl::DecisionForestTrainer<FeatureType, DataSet, LabelType, ExampleIndex, NodeType>::
train(pcl::DecisionForest<NodeType>& forest)
{
for (std::size_t tree_index = 0; tree_index < num_of_trees_to_train_; ++tree_index) {
pcl::DecisionTree<NodeType> tree;
decision_tree_trainer_.train(tree);
forest.push_back(tree);
}
}
pcl::DecisionTree
Class representing a decision tree.
Definition: decision_tree.h:49
pcl::DecisionForest
Class representing a decision forest.
Definition: decision_forest.h:51
pcl::DecisionForestTrainer::train
void train(DecisionForest< NodeType > &forest)
Trains a decision forest using the set training data and settings.
Definition: decision_forest_trainer.hpp:66
pcl::DecisionForestTrainer::~DecisionForestTrainer
virtual ~DecisionForestTrainer()
Destructor.
Definition: decision_forest_trainer.hpp:56
pcl::DecisionForestTrainer::DecisionForestTrainer
DecisionForestTrainer()
Constructor.
Definition: decision_forest_trainer.hpp:46