Changeset 1112 for trunk/doc/concepts.doxygen

Timestamp:

Feb 21, 2008, 3:59:30 PM (15 years ago)

Author:

Markus Ringnér

Message:

Mostly related to #295 and #182

File:

• trunk/doc/concepts.doxygen (modified) (2 diffs)

trunk/doc/concepts.doxygen

@@ -5 +5 @@
 // This file is part of the yat library, http://trac.thep.lu.se/yat
 //
-// The yat library is free software; you can redistribute it and/or
+// The yat library is free software; you can redistribute it and./or
 // modify it under the terms of the GNU General Public License as
 // published by the Free Software Foundation; either version 2 of the
@@ -22 +22 @@
 
 /**
- \page Concepts Concepts
+\page Concepts Concepts
 
- This page lists all the C++ concepts in the yat project.
+This page lists all the C++ concepts in the yat project.
 
- - \subpage concept_distance
+- \subpage concept_distance
+- \subpage concept_neighbor_weighting
 */
 
 
 /**
- \page concept_distance Distance
- \section Description
- Distance is a concept ...
- \section Requirements
- Classes implementing the concept Distance should fulfill ... 
- Examples include theplu::yat::statistics::PearsonDistance and theplu::yat::statistics::EuclideanDistance.
+\page concept_distance Distance
+
+\section Description
+
+\ref concept_distance is a concept ..
+
+\section Requirements
+
+Classes modelling the concept \ref concept_distance should implement ...  
+
+Examples of classes modelling the concept \ref concept_distance
+include theplu::yat::statistics::PearsonDistance and
+theplu::yat::statistics::EuclideanDistance.
+
 */
+
+/**
+\page concept_neighbor_weighting Neighbor Weighting Method
+
+\section Description
+
+\ref concept_neighbor_weighting is a concept used in connection with
+theplu::yat::classifier::KNN - classes used as the template argument
+NeighborWeighting should implement this concept.
+
+\section Requirements
+
+Classes modelling the concept \ref concept_neighbor_weighting should
+implement the following function:
+  
+\verbatim   
+void operator()(const utility::VectorBase& distance, const std::vector<size_t> k_sorted,
+                const Target& target, utility::VectorMutable& prediction) const
+\endverbatim
+
+For a test sample, this function should calculate a total vote
+(i.e. based on all k nearest neighbors) for each class. The vector \a
+distance contains the distances from a test sample to all training
+samples. The vector \a k_sorted contains the indices (for both \a
+distance and \a target) to the k training samples with the smallest
+distances to the test sample. The class for each training sample is
+given by \a target, which is sorted in the same sample order as \a
+distance. For each class the function calculates a total vote based on
+the the nearest neighbors of the test sample that belong to the
+class. The total vote for each class is stored in the vector \a prediction.
+
+Examples of classes modelling the concept \ref
+concept_neighbor_weighting include
+theplu::yat::classifier::KNN_Uniform,
+theplu::yat::classifier::KNN_ReciprocalDistance and
+theplu::yat::classifier::KNN_ReciprocalRank.
+
+*/