Point Cloud Library (PCL) 1.13.0
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stats_estimator.h
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37
38#pragma once
39
40#include <pcl/common/common.h>
41
42#include <ostream>
43#include <vector>
44
45namespace pcl {
46
47/** Class interface for gathering statistics for decision tree learning. */
48template <class LabelDataType, class NodeType, class DataSet, class ExampleIndex>
49class PCL_EXPORTS StatsEstimator {
50
51public:
52 /** Destructor. */
53 virtual ~StatsEstimator() = default;
54
55 /** Returns the number of brances a node can have (e.g. a binary tree has 2). */
56 virtual std::size_t
57 getNumOfBranches() const = 0;
58
59 /** Computes and sets the statistics for a node.
60 *
61 * \param[in] data_set the data set used for training
62 * \param[in] examples the examples used for computing the statistics for the
63 * specified node
64 * \param[in] label_data the labels corresponding to the examples
65 * \param[out] node The destination node for the statistics
66 */
67 virtual void
68 computeAndSetNodeStats(DataSet& data_set,
69 std::vector<ExampleIndex>& examples,
70 std::vector<LabelDataType>& label_data,
71 NodeType& node) const = 0;
72
73 /** Returns the label of the specified node.
74 *
75 * \param[in] node The node from which the label is extracted
76 */
77 virtual LabelDataType
78 getLabelOfNode(NodeType& node) const = 0;
79
80 /** Computes the information gain obtained by the specified threshold on the supplied
81 * feature evaluation results.
82 *
83 * \param[in] data_set the data set used for extracting the supplied result values.
84 * \param[in] examples the examples used to extract the supplied result values
85 * \param[in] label_data the labels corresponding to the examples
86 * \param[in] results the results obtained from the feature evaluation
87 * \param[in] flags the flags obtained together with the results
88 * \param[in] threshold the threshold which is used to compute the information gain
89 */
90 virtual float
91 computeInformationGain(DataSet& data_set,
92 std::vector<ExampleIndex>& examples,
93 std::vector<LabelDataType>& label_data,
94 std::vector<float>& results,
95 std::vector<unsigned char>& flags,
96 const float threshold) const = 0;
97
98 /** Computes the branch indices obtained by the specified threshold on the supplied
99 * feature evaluation results.
100 *
101 * \param[in] results the results obtained from the feature evaluation
102 * \param[in] flags the flags obtained together with the results.
103 * \param[in] threshold the threshold which is used to compute the branch indices
104 * \param[out] branch_indices the destination for the computed branch indices.
105 */
106 virtual void
107 computeBranchIndices(std::vector<float>& results,
108 std::vector<unsigned char>& flags,
109 const float threshold,
110 std::vector<unsigned char>& branch_indices) const = 0;
111
112 /** Computes the branch indices obtained by the specified threshold on the supplied
113 * feature evaluation results.
114 *
115 * \param[in] result the result obtained from the feature evaluation
116 * \param[in] flag the flag obtained together with the result
117 * \param[in] threshold the threshold which is used to compute the branch index
118 * \param[out] branch_index the destination for the computed branch index
119 */
120 virtual void
121 computeBranchIndex(const float result,
122 const unsigned char flag,
123 const float threshold,
124 unsigned char& branch_index) const = 0;
125
126 /** Generates code for computing the branch indices for the specified node and writes
127 * it to the specified stream.
128 *
129 * \param[in] node the node for which the branch index estimation code is generated
130 * \param[out] stream the destination for the code
131 */
132 virtual void
133 generateCodeForBranchIndexComputation(NodeType& node, std::ostream& stream) const = 0;
134
135 /** Generates code for computing the output for the specified node and writes it to
136 * the specified stream.
137 *
138 * \param[in] node the node for which the output estimation code is generated
139 * \param[out] stream the destination for the code
140 */
141 virtual void
142 generateCodeForOutput(NodeType& node, std::ostream& stream) const = 0;
143};
144
145} // namespace pcl
Class interface for gathering statistics for decision tree learning.
virtual std::size_t getNumOfBranches() const =0
Returns the number of brances a node can have (e.g.
virtual float computeInformationGain(DataSet &data_set, std::vector< ExampleIndex > &examples, std::vector< LabelDataType > &label_data, std::vector< float > &results, std::vector< unsigned char > &flags, const float threshold) const =0
Computes the information gain obtained by the specified threshold on the supplied feature evaluation ...
virtual void generateCodeForOutput(NodeType &node, std::ostream &stream) const =0
Generates code for computing the output for the specified node and writes it to the specified stream.
virtual void generateCodeForBranchIndexComputation(NodeType &node, std::ostream &stream) const =0
Generates code for computing the branch indices for the specified node and writes it to the specified...
virtual void computeAndSetNodeStats(DataSet &data_set, std::vector< ExampleIndex > &examples, std::vector< LabelDataType > &label_data, NodeType &node) const =0
Computes and sets the statistics for a node.
virtual LabelDataType getLabelOfNode(NodeType &node) const =0
Returns the label of the specified node.
virtual ~StatsEstimator()=default
Destructor.
virtual void computeBranchIndices(std::vector< float > &results, std::vector< unsigned char > &flags, const float threshold, std::vector< unsigned char > &branch_indices) const =0
Computes the branch indices obtained by the specified threshold on the supplied feature evaluation re...
virtual void computeBranchIndex(const float result, const unsigned char flag, const float threshold, unsigned char &branch_index) const =0
Computes the branch indices obtained by the specified threshold on the supplied feature evaluation re...
Define standard C methods and C++ classes that are common to all methods.