Point Cloud Library (PCL) 1.12.0
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Utility class for evaluating a decision tree. More...
#include <pcl/ml/dt/decision_tree_evaluator.h>
Utility class for evaluating a decision tree.
Definition at line 55 of file decision_tree_evaluator.h.
pcl::DecisionTreeEvaluator< FeatureType, DataSet, LabelType, ExampleIndex, NodeType >::DecisionTreeEvaluator | ( | ) |
Constructor.
Definition at line 54 of file decision_tree_evaluator.hpp.
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virtual |
Destructor.
Definition at line 63 of file decision_tree_evaluator.hpp.
void pcl::DecisionTreeEvaluator< FeatureType, DataSet, LabelType, ExampleIndex, NodeType >::evaluate | ( | pcl::DecisionTree< NodeType > & | tree, |
pcl::FeatureHandler< FeatureType, DataSet, ExampleIndex > & | feature_handler, | ||
pcl::StatsEstimator< LabelType, NodeType, DataSet, ExampleIndex > & | stats_estimator, | ||
DataSet & | data_set, | ||
ExampleIndex | example, | ||
NodeType & | leave ) |
Evaluates the specified examples using the supplied tree.
[in] | tree | the decision tree |
[in] | feature_handler | the feature handler used to train the tree |
[in] | stats_estimator | the statistics estimation instance used while training the tree |
[in] | data_set | the data set used for evaluation |
[in] | example | the example that has to be evaluated |
[out] | leave | The leave reached by the examples. |
Definition at line 147 of file decision_tree_evaluator.hpp.
References pcl::ConstCloudIterator< PointT >::ConstCloudIterator().
void pcl::DecisionTreeEvaluator< FeatureType, DataSet, LabelType, ExampleIndex, NodeType >::evaluate | ( | pcl::DecisionTree< NodeType > & | tree, |
pcl::FeatureHandler< FeatureType, DataSet, ExampleIndex > & | feature_handler, | ||
pcl::StatsEstimator< LabelType, NodeType, DataSet, ExampleIndex > & | stats_estimator, | ||
DataSet & | data_set, | ||
std::vector< ExampleIndex > & | examples, | ||
std::vector< LabelType > & | label_data ) |
Evaluates the specified examples using the supplied tree.
[in] | tree | the decision tree |
[in] | feature_handler | the feature handler used to train the tree |
[in] | stats_estimator | the statistics estimation instance used while training the tree |
[in] | data_set | the data set used for evaluation |
[in] | examples | the examples that have to be evaluated |
[out] | label_data | the destination for the resulting label data |
Definition at line 73 of file decision_tree_evaluator.hpp.
References pcl::ConstCloudIterator< PointT >::ConstCloudIterator(), and pcl::ConstCloudIterator< PointT >::size().
void pcl::DecisionTreeEvaluator< FeatureType, DataSet, LabelType, ExampleIndex, NodeType >::evaluateAndAdd | ( | pcl::DecisionTree< NodeType > & | tree, |
pcl::FeatureHandler< FeatureType, DataSet, ExampleIndex > & | feature_handler, | ||
pcl::StatsEstimator< LabelType, NodeType, DataSet, ExampleIndex > & | stats_estimator, | ||
DataSet & | data_set, | ||
std::vector< ExampleIndex > & | examples, | ||
std::vector< LabelType > & | label_data ) |
Evaluates the specified examples using the supplied tree and adds the results to the supplied results array.
[in] | tree | the decision tree |
[in] | feature_handler | the feature handler used to train the tree |
[in] | stats_estimator | the statistics estimation instance used while training the tree |
[in] | data_set | the data set used for evaluation |
[in] | examples | the examples that have to be evaluated |
[out] | label_data | the destination where the resulting label data is added to |
Definition at line 110 of file decision_tree_evaluator.hpp.
References pcl::ConstCloudIterator< PointT >::ConstCloudIterator(), and pcl::ConstCloudIterator< PointT >::size().
void pcl::DecisionTreeEvaluator< FeatureType, DataSet, LabelType, ExampleIndex, NodeType >::getNodes | ( | pcl::DecisionTree< NodeType > & | tree, |
pcl::FeatureHandler< FeatureType, DataSet, ExampleIndex > & | feature_handler, | ||
pcl::StatsEstimator< LabelType, NodeType, DataSet, ExampleIndex > & | stats_estimator, | ||
DataSet & | data_set, | ||
std::vector< ExampleIndex > & | examples, | ||
std::vector< NodeType * > & | nodes ) |
Evaluates the specified examples using the supplied tree.
[in] | tree | the decision tree |
[in] | feature_handler | the feature handler used to train the tree |
[in] | stats_estimator | the statistics estimation instance used while training the tree |
[in] | data_set | the data set used for evaluation |
[in] | examples | the examples that have to be evaluated |
[out] | nodes | the leaf-nodes reached while evaluation |
Definition at line 180 of file decision_tree_evaluator.hpp.
References pcl::ConstCloudIterator< PointT >::ConstCloudIterator(), and pcl::ConstCloudIterator< PointT >::size().