source: libs/magicsquares/src/LDAClassifier.cpp @ 1706

Revision 90, 1.9 KB checked in by dave, 11 years ago (diff)

PCA updated - projection and resynthesis seem to work

Line 
1// Copyright (C) 2009 foam
2//
3// This program is free software; you can redistribute it and/or modify
4// it under the terms of the GNU General Public License as published by
5// the Free Software Foundation; either version 2 of the License, or
6// (at your option) any later version.
7//
8// This program is distributed in the hope that it will be useful,
9// but WITHOUT ANY WARRANTY; without even the implied warranty of
10// MERCHANTABILITY or FITNESS FOR A PARTICULAR PURPOSE.  See the
11// GNU General Public License for more details.
12//
13// You should have received a copy of the GNU General Public License
14// along with this program; if not, write to the Free Software
15// Foundation, Inc., 59 Temple Place - Suite 330, Boston, MA 02111-1307, USA.
16
17#include "LDAClassifier.h"
18
19LDAClassifier::LDAClassifier(unsigned int FeatureSize) :
20Classifier(FeatureSize)
21{
22}
23
24LDAClassifier::~LDAClassifier()
25{
26}
27
28int LDAClassifier::Classify(const Vector<float> &v)
29{
30        return 0;
31}
32
33void LDAClassifier::CalcGroupMeans()
34{       
35        for (GroupMap::iterator i=m_Groups.begin();
36                i!=m_Groups.end(); ++i)
37        {
38                m_GroupMean[i->first]=Vector<float>(m_FeatureSize);
39                m_GroupMean[i->first].Zero();           
40                for (FeatureVec::iterator vi = i->second.begin(); vi!=i->second.end(); ++vi)
41                {
42                        m_GroupMean[i->first]+=*vi;
43                }               
44                m_GroupMean[i->first]/=i->second.size();
45        }
46}
47
48void LDAClassifier::CalcMeanCorrected()
49{       
50/*      CalcMean();
51       
52        // copy the training data :/
53        m_MeanCorrectedGroups = m_Groups;
54       
55        for (GroupMap::iterator i=m_MeanCorrectedGroups.begin();
56                i!=m_MeanCorrectedGroups.end(); ++i)
57        {
58                Matrix<float> Group(i->second.size(), m_FeatureSize);
59                unsigned int count=0;
60                for (FeatureVec::iterator vi = i->second.begin(); vi!=i->second.end(); ++vi)
61                {
62                        Group.SetRowVector(count++,*vi);
63                }
64                m_MeanCorrectedGroups[i->first]=Group;
65        }*/
66}
67
68void LDAClassifier::CalcGroupCovariance()
69{
70       
71}
72
73void LDAClassifier::CalcPooledCovariance()
74{
75}
76
77void LDAClassifier::CalcPriorProbablity()
78{
79}
80
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