1
2
3
4
5
6
7
8
9
10
11
12
13
14
15
16
17
18
19
20
21
22
23
24
25
26
27
28
29
30
31
32
33
34
35
36
37
38
39
40
41
42
43
44
45
46
47
48
49
50
51
52
53
54
55
56
57
58
59
60
61
62
63
64
65
66
67
68
69
70
71
72
73
74
75
76
77
78
79
80
81
82
83
84
85
86
87
88
89
90
91
92
93
94
95
96
97
98
99
100
101
102
103
104
105
106
107
108
109
110
111
112
113
114
115
116
117
118
119
120
121
122
123
124
125
126
127
128
|
/*********************************************************************
MLDemos: A User-Friendly visualization toolkit for machine learning
Copyright (C) 2010 Basilio Noris
Contact: mldemos@b4silio.com
Evolution-Strategy Mixture of Logisitics Regression
Copyright (C) 2011 Stephane Magnenat
Contact: stephane at magnenat dot net
This library is free software; you can redistribute it and/or
modify it under the terms of the GNU Lesser General Public License,
version 3 as published by the Free Software Foundation.
This library is distributed in the hope that it will be useful, but
WITHOUT ANY WARRANTY; without even the implied warranty of
MERCHANTABILITY or FITNESS FOR A PARTICULAR PURPOSE. See the GNU
Lesser General Public License for more details.
You should have received a copy of the GNU Lesser General Public
License along with this library; if not, write to the Free
Software Foundation, Inc., 675 Mass Ave, Cambridge, MA 02139, USA.
*********************************************************************/
#include "interfaceRRMLRClassifier.h"
#include "classifierRRMLR.h"
#include "ui_paramsRRMLR.h"
#include <cassert>
using namespace std;
ClassRRMLR::ClassRRMLR()
{
params = new Ui::ParametersRRMLR();
params->setupUi(widget = new QWidget());
}
void ClassRRMLR::SetParams(Classifier *classifier)
{
if(!classifier) return;
const u32 cutCount = params->rrmlrCutSpin->value();
const float alpha = params->rrmlrAlphaSpin->value();
const u32 restartCount = params->rrmlrRestartSpin->value();
const u32 maxIter = params->rrmlrMaxIterSpin->value();
ClassifierRRMLR* c(dynamic_cast<ClassifierRRMLR*>(classifier));
assert(c);
c->SetParams(cutCount, alpha, restartCount, maxIter);
}
QString ClassRRMLR::GetAlgoString()
{
const u32 cutCount = params->rrmlrCutSpin->value();
const float alpha = params->rrmlrAlphaSpin->value();
const u32 restartCount = params->rrmlrRestartSpin->value();
const u32 maxIter = params->rrmlrMaxIterSpin->value();
return QString("RRMLR %1 %2 %3 %4").arg(cutCount).arg(alpha).arg(restartCount).arg(maxIter);
}
Classifier *ClassRRMLR::GetClassifier()
{
ClassifierRRMLR *classifier = new ClassifierRRMLR();
SetParams(classifier);
return classifier;
}
void ClassRRMLR::DrawModel(Canvas *canvas, QPainter &painter, Classifier *classifier)
{
if(!classifier || !canvas)
return;
painter.setRenderHint(QPainter::Antialiasing, true);
int posClass = 1;
FOR(i, canvas->data->GetCount())
{
const fvec sample = canvas->data->GetSample(i);
const int label = canvas->data->GetLabel(i);
const QPointF point = canvas->toCanvasCoords(canvas->data->GetSample(i));
const float response = classifier->Test(sample);
if(response > 0)
{
if(label == posClass)
Canvas::drawSample(painter, point, 9, 1);
else
Canvas::drawCross(painter, point, 6, 2);
}
else
{
if(label != posClass)
Canvas::drawSample(painter, point, 9, 0);
else
Canvas::drawCross(painter, point, 6, 0);
}
}
}
void ClassRRMLR::SaveOptions(QSettings &settings)
{
settings.setValue("rrmlrCut", params->rrmlrCutSpin->value());
settings.setValue("rrmlrAlpha", params->rrmlrAlphaSpin->value());
settings.setValue("rrmlrRestart", params->rrmlrRestartSpin->value());
settings.setValue("rrmlrMaxIter", params->rrmlrMaxIterSpin->value());
}
bool ClassRRMLR::LoadOptions(QSettings &settings)
{
if(settings.contains("rrmlrCut")) params->rrmlrCutSpin->setValue(settings.value("rrmlrCut").toUInt());
if(settings.contains("rrmlrAlpha")) params->rrmlrAlphaSpin->setValue(settings.value("rrmlrAlpha").toFloat());
if(settings.contains("rrmlrRestart")) params->rrmlrRestartSpin->setValue(settings.value("rrmlrRestart").toUInt());
if(settings.contains("rrmlrMaxIter")) params->rrmlrMaxIterSpin->setValue(settings.value("rrmlrMaxIter").toUInt());
return true;
}
void ClassRRMLR::SaveParams(QTextStream &file)
{
file << "classificationOptions" << ":" << "rrmlrCut" << " " << params->rrmlrCutSpin->value() << "\n";
file << "classificationOptions" << ":" << "rrmlrAlpha" << " " << params->rrmlrAlphaSpin->value() << "\n";
file << "classificationOptions" << ":" << "rrmlrRestart" << " " << params->rrmlrRestartSpin->value() << "\n";
file << "classificationOptions" << ":" << "rrmlrMaxIter" << " " << params->rrmlrMaxIterSpin->value() << "\n";
}
bool ClassRRMLR::LoadParams(QString name, float value)
{
if(name.endsWith("rrmlrCut")) params->rrmlrCutSpin->setValue((int)value);
if(name.endsWith("rrmlrAlpha")) params->rrmlrAlphaSpin->setValue(value);
if(name.endsWith("rrmlrRestart")) params->rrmlrRestartSpin->setValue((int)value);
if(name.endsWith("rrmlrMaxIter")) params->rrmlrMaxIterSpin->setValue((int)value);
return true;
}
|
