Point Cloud Library (PCL)  1.14.1-dev
decision_tree_evaluator.h
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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 
47 namespace pcl {
48 
49 /** Utility class for evaluating a decision tree. */
50 template <class FeatureType,
51  class DataSet,
52  class LabelType,
53  class ExampleIndex,
54  class NodeType>
56 
57 public:
58  /** Constructor. */
60 
61  /** Destructor. */
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
75  evaluate(
79  DataSet& data_set,
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
99  DataSet& data_set,
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(
118  DataSet& data_set,
119  ExampleIndex example,
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(
137  DataSet& data_set,
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>
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.
DecisionTreeEvaluator()
Constructor.
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.
Class representing a decision tree.
Definition: decision_tree.h:49
Utility class interface which is used for creating and evaluating features.
Define standard C methods and C++ classes that are common to all methods.