Point Cloud Library (PCL) 1.12.0
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decision_tree_evaluator.h
1/*
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37
38#pragma once
39
40#include <pcl/common/common.h>
41#include <pcl/ml/dt/decision_tree.h>
42#include <pcl/ml/feature_handler.h>
43#include <pcl/ml/stats_estimator.h>
44
45#include <vector>
46
47namespace pcl {
48
49/** Utility class for evaluating a decision tree. */
50template <class FeatureType,
51 class DataSet,
52 class LabelType,
53 class ExampleIndex,
54 class NodeType>
56
57public:
58 /** Constructor. */
60
61 /** Destructor. */
62 virtual ~DecisionTreeEvaluator();
63
64 /** Evaluates the specified examples using the supplied tree.
65 *
66 * \param[in] tree the decision tree
67 * \param[in] feature_handler the feature handler used to train the tree
68 * \param[in] stats_estimator the statistics estimation instance used while training
69 * the tree
70 * \param[in] data_set the data set used for evaluation
71 * \param[in] examples the examples that have to be evaluated
72 * \param[out] label_data the destination for the resulting label data
73 */
74 void
80 std::vector<ExampleIndex>& examples,
81 std::vector<LabelType>& label_data);
82
83 /** Evaluates the specified examples using the supplied tree and adds the
84 * results to the supplied results array.
85 *
86 * \param[in] tree the decision tree
87 * \param[in] feature_handler the feature handler used to train the tree
88 * \param[in] stats_estimator the statistics estimation instance used while training
89 * the tree
90 * \param[in] data_set the data set used for evaluation
91 * \param[in] examples the examples that have to be evaluated
92 * \param[out] label_data the destination where the resulting label data is added to
93 */
94 void
100 std::vector<ExampleIndex>& examples,
101 std::vector<LabelType>& label_data);
102
103 /** Evaluates the specified examples using the supplied tree.
104 *
105 * \param[in] tree the decision tree
106 * \param[in] feature_handler the feature handler used to train the tree
107 * \param[in] stats_estimator the statistics estimation instance used while training
108 * the tree
109 * \param[in] data_set the data set used for evaluation
110 * \param[in] example the example that has to be evaluated
111 * \param[out] leave The leave reached by the examples.
112 */
113 void
114 evaluate(
120 NodeType& leave);
121
122 /** Evaluates the specified examples using the supplied tree.
123 *
124 * \param[in] tree the decision tree
125 * \param[in] feature_handler the feature handler used to train the tree
126 * \param[in] stats_estimator the statistics estimation instance used while training
127 * the tree
128 * \param[in] data_set the data set used for evaluation
129 * \param[in] examples the examples that have to be evaluated
130 * \param[out] nodes the leaf-nodes reached while evaluation
131 */
132 void
133 getNodes(
138 std::vector<ExampleIndex>& examples,
139 std::vector<NodeType*>& nodes);
140};
141
142} // namespace pcl
143
144#include <pcl/ml/impl/dt/decision_tree_evaluator.hpp>
Iterator class for point clouds with or without given indices.
Utility class for evaluating a decision tree.
virtual ~DecisionTreeEvaluator()
Destructor.
void 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.
void 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...
void 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.
Define standard C methods and C++ classes that are common to all methods.