source: trunk/yat/classifier/KNN_ReciprocalRank.cc @ 2881

Last change on this file since 2881 was 2881, checked in by Peter, 9 years ago

Define PP variables in config.h rather than in CPPFLAGS. Include
config.h into all source files. Only ammend CXXFLAGS with '-Wall
-pedantic' when --enable-debug. In default mode we respect CXXFLAGS
value set by user, or set to default value '-O3'.

  • Property svn:eol-style set to native
  • Property svn:keywords set to Id
File size: 1.4 KB
Line 
1// $Id: KNN_ReciprocalRank.cc 2881 2012-11-18 01:28:05Z peter $
2
3/*
4  Copyright (C) 2008 Jari Häkkinen, Peter Johansson, Markus Ringnér
5
6  This file is part of the yat library, http://dev.thep.lu.se/yat
7
8  The yat library is free software; you can redistribute it and/or
9  modify it under the terms of the GNU General Public License as
10  published by the Free Software Foundation; either version 3 of the
11  License, or (at your option) any later version.
12
13  The yat library is distributed in the hope that it will be useful,
14  but WITHOUT ANY WARRANTY; without even the implied warranty of
15  MERCHANTABILITY or FITNESS FOR A PARTICULAR PURPOSE. See the GNU
16  General Public License for more details.
17
18  You should have received a copy of the GNU General Public License
19  along with yat. If not, see <http://www.gnu.org/licenses/>.
20*/
21
22#include <config.h>
23
24#include "KNN_ReciprocalRank.h"
25#include "Target.h"
26
27#include "yat/utility/VectorBase.h"
28#include "yat/utility/VectorMutable.h"
29
30#include <cmath>
31#include <vector>
32
33namespace theplu {
34namespace yat {
35namespace classifier {
36
37  void KNN_ReciprocalRank::operator()(const utility::VectorBase& distance,
38                                      const std::vector<size_t>& k_sorted, 
39                                      const Target& target, 
40                                      utility::VectorMutable& prediction) const
41  {           
42    for(size_t j=0;j<k_sorted.size();j++) 
43      if(!std::isinf(distance(k_sorted[j])))
44         prediction(target(k_sorted[j]))+=1.0/(j+1);               
45  }
46
47}}}
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