Point Cloud Library (PCL)  1.9.1
decision_forest_evaluator.h
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37 
38 #ifndef PCL_ML_DT_DECISION_FOREST_EVALUATOR_H_
39 #define PCL_ML_DT_DECISION_FOREST_EVALUATOR_H_
40 
41 #include <pcl/common/common.h>
42 
43 #include <pcl/ml/dt/decision_tree_evaluator.h>
44 #include <pcl/ml/dt/decision_forest.h>
45 #include <pcl/ml/feature_handler.h>
46 #include <pcl/ml/stats_estimator.h>
47 
48 #include <vector>
49 
50 namespace pcl
51 {
52 
53  /** \brief Utility class for evaluating a decision forests. */
54  template <
55  class FeatureType,
56  class DataSet,
57  class LabelType,
58  class ExampleIndex,
59  class NodeType >
61  {
62  public:
63  /** \brief Constructor. */
65  /** \brief Destructor. */
66  virtual
68 
69  /** \brief Evaluates the specified examples using the supplied forest.
70  * \param[in] DecisionForestEvaluator The decision forest.
71  * \param[in] feature_handler The feature handler used to train the tree.
72  * \param[in] stats_estimator The statistics estimation instance used while training the tree.
73  * \param[in] data_set The data set used for evaluation.
74  * \param[in] examples The examples that have to be evaluated.
75  * \param[out] label_data The destination for the resulting label data.
76  */
77  void
81  DataSet & data_set,
82  std::vector<ExampleIndex> & examples,
83  std::vector<LabelType> & label_data);
84 
85  /** \brief Evaluates a specific patch using the supplied forest.
86  * \param[in] DecisionForestEvaluator The decision forest.
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 the tree.
89  * \param[in] data_set The data set used for evaluation.
90  * \param[in] example The examples that have to be evaluated.
91  * \param[out] leaves The leaves where the patch arrives
92  */
93  void
97  DataSet & data_set,
98  ExampleIndex example,
99  std::vector<NodeType> & leaves);
100 
101  private:
102  /** \brief Evaluator for decision trees. */
104  };
105 
106 }
107 
108 #include <pcl/ml/impl/dt/decision_forest_evaluator.hpp>
109 
110 #endif
Class representing a decision forest.
Utility class for evaluating a decision tree.
This file defines compatibility wrappers for low level I/O functions.
Definition: convolution.h:45
Define standard C methods and C++ classes that are common to all methods.
void evaluate(pcl::DecisionForest< NodeType > &DecisionForestEvaluator, 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 forest.
Utility class for evaluating a decision forests.
Utility class interface which is used for creating and evaluating features.