| 1 | // $Id: concepts.doxygen 1275 2008-04-11 06:10:12Z jari $ |
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| 2 | // |
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| 3 | // Copyright (C) 2008 Peter Johansson, Markus Ringnér |
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| 4 | // |
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| 5 | // This file is part of the yat library, http://trac.thep.lu.se/yat |
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| 6 | // |
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| 7 | // The yat library is free software; you can redistribute it and/or |
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| 8 | // modify it under the terms of the GNU General Public License as |
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| 9 | // published by the Free Software Foundation; either version 2 of the |
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| 10 | // License, or (at your option) any later version. |
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| 11 | // |
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| 12 | // The yat library is distributed in the hope that it will be useful, |
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| 13 | // but WITHOUT ANY WARRANTY; without even the implied warranty of |
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| 14 | // MERCHANTABILITY or FITNESS FOR A PARTICULAR PURPOSE. See the GNU |
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| 15 | // General Public License for more details. |
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| 16 | // |
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| 17 | // You should have received a copy of the GNU General Public License |
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| 18 | // along with this program; if not, write to the Free Software |
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| 19 | // Foundation, Inc., 59 Temple Place - Suite 330, Boston, MA |
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| 20 | // 02111-1307, USA. |
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| 21 | |
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| 22 | |
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| 23 | /** |
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| 24 | \page Concepts Concepts |
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| 25 | |
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| 26 | This page lists all the C++ concepts in the yat project. |
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| 27 | |
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| 28 | - \subpage concept_distance |
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| 29 | - \subpage concept_neighbor_weighting |
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| 30 | */ |
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| 31 | |
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| 32 | |
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| 33 | /** |
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| 34 | \page concept_distance Distance |
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| 35 | |
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| 36 | \section Description |
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| 37 | |
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| 38 | \ref concept_distance is a concept for classes implementing different |
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| 39 | alternatives to calculate the distance between two points. |
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| 40 | |
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| 41 | \section Requirements |
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| 42 | |
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| 43 | Classes modelling the concept \ref concept_distance should implement |
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| 44 | the following public function: |
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| 45 | |
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| 46 | \verbatim |
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| 47 | template<typename Iter1, typename Iter2> |
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| 48 | double operator() (Iter1 beg1, Iter1 end1, Iter2 beg2) const |
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| 49 | \endverbatim |
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| 50 | |
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| 51 | This function should calculate and return the distance between |
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| 52 | elements of two ranges. The first range is given by [\a beg1, \a end1) |
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| 53 | and the second range starts with \a beg2 and has the same length as |
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| 54 | the first range. The function should support iterators of the category |
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| 55 | std::forward_iterator. The function should provide both a fast |
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| 56 | calculation for unweighted iterators and a calculation for weighted |
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| 57 | iterators. The latter correspond to the case where elements in a range |
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| 58 | have both a value and a weight. The selection between unweighted and |
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| 59 | weighted implementations should utilize |
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| 60 | theplu::yat::utility::unweighted_iterator_tag and |
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| 61 | theplu::yat::utility::weighted_iterator_tag. Moreover |
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| 62 | theplu::yat::utility::weighted_if_any2 should be utilized to provide a |
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| 63 | weighted implementation if any of the two ranges is weighted, and an |
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| 64 | unweighted implementation when both ranges are unweighted. |
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| 65 | |
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| 66 | \section Implementations |
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| 67 | |
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| 68 | Examples of classes modelling the concept \ref concept_distance |
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| 69 | include theplu::yat::statistics::PearsonDistance and |
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| 70 | theplu::yat::statistics::EuclideanDistance. |
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| 71 | |
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| 72 | \see \ref weighted_distance |
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| 73 | |
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| 74 | */ |
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| 75 | |
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| 76 | /** |
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| 77 | \page concept_neighbor_weighting Neighbor Weighting Method |
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| 78 | |
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| 79 | \section Description |
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| 80 | |
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| 81 | \ref concept_neighbor_weighting is a concept used in connection with |
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| 82 | theplu::yat::classifier::KNN - classes used as the template argument |
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| 83 | NeighborWeighting should implement this concept. |
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| 84 | |
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| 85 | \section Requirements |
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| 86 | |
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| 87 | Classes modelling the concept \ref concept_neighbor_weighting should |
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| 88 | implement the following public function: |
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| 89 | |
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| 90 | \verbatim |
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| 91 | void operator()(const utility::VectorBase& distance, const std::vector<size_t> k_sorted, |
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| 92 | const Target& target, utility::VectorMutable& prediction) const |
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| 93 | \endverbatim |
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| 94 | |
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| 95 | For a test sample, this function should calculate a total vote |
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| 96 | (i.e. based on all k nearest neighbors) for each class. The vector \a |
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| 97 | distance contains the distances from a test sample to all training |
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| 98 | samples. The vector \a k_sorted contains the indices (for both \a |
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| 99 | distance and \a target) to the k training samples with the smallest |
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| 100 | distances to the test sample. The class for each training sample is |
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| 101 | given by \a target, which is sorted in the same sample order as \a |
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| 102 | distance. For each class the function calculates a total vote based on |
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| 103 | the the nearest neighbors of the test sample that belong to the |
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| 104 | class. The total vote for each class is stored in the vector \a |
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| 105 | prediction. The function should be implemented such that nearest |
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| 106 | neighbors with distance infinity do not vote. |
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| 107 | |
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| 108 | \section Implementations |
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| 109 | |
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| 110 | Examples of classes modelling the concept \ref |
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| 111 | concept_neighbor_weighting include |
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| 112 | theplu::yat::classifier::KNN_Uniform, |
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| 113 | theplu::yat::classifier::KNN_ReciprocalDistance and |
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| 114 | theplu::yat::classifier::KNN_ReciprocalRank. |
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| 115 | |
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| 116 | */ |
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