146 lines
5.9 KiB
C
146 lines
5.9 KiB
C
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/*
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* Software License Agreement (BSD License)
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*
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* Point Cloud Library (PCL) - www.pointclouds.org
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* Copyright (c) 2010-2011, Willow Garage, Inc.
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*
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* All rights reserved.
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*
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* Redistribution and use in source and binary forms, with or without
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* modification, are permitted provided that the following conditions
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* are met:
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*
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* * Redistributions of source code must retain the above copyright
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* notice, this list of conditions and the following disclaimer.
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* * Redistributions in binary form must reproduce the above
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* copyright notice, this list of conditions and the following
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* disclaimer in the documentation and/or other materials provided
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* with the distribution.
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* * Neither the name of Willow Garage, Inc. nor the names of its
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* contributors may be used to endorse or promote products derived
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* from this software without specific prior written permission.
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*
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* THIS SOFTWARE IS PROVIDED BY THE COPYRIGHT HOLDERS AND CONTRIBUTORS
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* "AS IS" AND ANY EXPRESS OR IMPLIED WARRANTIES, INCLUDING, BUT NOT
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* LIMITED TO, THE IMPLIED WARRANTIES OF MERCHANTABILITY AND FITNESS
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* FOR A PARTICULAR PURPOSE ARE DISCLAIMED. IN NO EVENT SHALL THE
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* COPYRIGHT OWNER OR CONTRIBUTORS BE LIABLE FOR ANY DIRECT, INDIRECT,
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* INCIDENTAL, SPECIAL, EXEMPLARY, OR CONSEQUENTIAL DAMAGES (INCLUDING,
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* BUT NOT LIMITED TO, PROCUREMENT OF SUBSTITUTE GOODS OR SERVICES;
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* LOSS OF USE, DATA, OR PROFITS; OR BUSINESS INTERRUPTION) HOWEVER
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* CAUSED AND ON ANY THEORY OF LIABILITY, WHETHER IN CONTRACT, STRICT
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* LIABILITY, OR TORT (INCLUDING NEGLIGENCE OR OTHERWISE) ARISING IN
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* ANY WAY OUT OF THE USE OF THIS SOFTWARE, EVEN IF ADVISED OF THE
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* POSSIBILITY OF SUCH DAMAGE.
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*
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*/
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#pragma once
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#include <pcl/common/common.h>
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#include <ostream>
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#include <vector>
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namespace pcl {
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/** Class interface for gathering statistics for decision tree learning. */
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template <class LabelDataType, class NodeType, class DataSet, class ExampleIndex>
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class PCL_EXPORTS StatsEstimator {
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public:
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/** Destructor. */
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virtual ~StatsEstimator(){};
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/** Returns the number of brances a node can have (e.g. a binary tree has 2). */
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virtual std::size_t
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getNumOfBranches() const = 0;
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/** Computes and sets the statistics for a node.
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*
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* \param[in] data_set the data set used for training
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* \param[in] examples the examples used for computing the statistics for the
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* specified node
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* \param[in] label_data the labels corresponding to the examples
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* \param[out] node The destination node for the statistics
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*/
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virtual void
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computeAndSetNodeStats(DataSet& data_set,
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std::vector<ExampleIndex>& examples,
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std::vector<LabelDataType>& label_data,
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NodeType& node) const = 0;
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/** Returns the label of the specified node.
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*
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* \param[in] node The node from which the label is extracted
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*/
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virtual LabelDataType
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getLabelOfNode(NodeType& node) const = 0;
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/** Computes the information gain obtained by the specified threshold on the supplied
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* feature evaluation results.
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*
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* \param[in] data_set the data set used for extracting the supplied result values.
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* \param[in] examples the examples used to extract the supplied result values
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* \param[in] label_data the labels corresponding to the examples
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* \param[in] results the results obtained from the feature evaluation
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* \param[in] flags the flags obtained together with the results
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* \param[in] threshold the threshold which is used to compute the information gain
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*/
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virtual float
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computeInformationGain(DataSet& data_set,
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std::vector<ExampleIndex>& examples,
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std::vector<LabelDataType>& label_data,
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std::vector<float>& results,
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std::vector<unsigned char>& flags,
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const float threshold) const = 0;
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/** Computes the branch indices obtained by the specified threshold on the supplied
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* feature evaluation results.
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*
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* \param[in] results the results obtained from the feature evaluation
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* \param[in] flags the flags obtained together with the results.
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* \param[in] threshold the threshold which is used to compute the branch indices
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* \param[out] branch_indices the destination for the computed branch indices.
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*/
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virtual void
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computeBranchIndices(std::vector<float>& results,
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std::vector<unsigned char>& flags,
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const float threshold,
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std::vector<unsigned char>& branch_indices) const = 0;
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/** Computes the branch indices obtained by the specified threshold on the supplied
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* feature evaluation results.
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*
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* \param[in] result the result obtained from the feature evaluation
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* \param[in] flag the flag obtained together with the result
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* \param[in] threshold the threshold which is used to compute the branch index
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* \param[out] branch_index the destination for the computed branch index
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*/
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virtual void
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computeBranchIndex(const float result,
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const unsigned char flag,
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const float threshold,
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unsigned char& branch_index) const = 0;
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/** Generates code for computing the branch indices for the specified node and writes
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* it to the specified stream.
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*
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* \param[in] node the node for which the branch index estimation code is generated
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* \param[out] stream the destination for the code
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*/
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virtual void
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generateCodeForBranchIndexComputation(NodeType& node, std::ostream& stream) const = 0;
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/** Generates code for computing the output for the specified node and writes it to
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* the specified stream.
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*
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* \param[in] node the node for which the output estimation code is generated
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* \param[out] stream the destination for the code
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*/
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virtual void
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generateCodeForOutput(NodeType& node, std::ostream& stream) const = 0;
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};
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} // namespace pcl
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