blob: d6ef7f5fb87cdb284624e95bd375e408d7dd4a06 (
plain)
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
|
package de.lmu.ifi.dbs.elki.utilities.scaling.outlier;
/*
This file is part of ELKI:
Environment for Developing KDD-Applications Supported by Index-Structures
Copyright (C) 2011
Ludwig-Maximilians-Universität München
Lehr- und Forschungseinheit für Datenbanksysteme
ELKI Development Team
This program is free software: you can redistribute it and/or modify
it under the terms of the GNU Affero General Public License as published by
the Free Software Foundation, either version 3 of the License, or
(at your option) any later version.
This program 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 Affero General Public License for more details.
You should have received a copy of the GNU Affero General Public License
along with this program. If not, see <http://www.gnu.org/licenses/>.
*/
import java.util.Arrays;
import de.lmu.ifi.dbs.elki.database.ids.DBID;
import de.lmu.ifi.dbs.elki.result.outlier.InvertedOutlierScoreMeta;
import de.lmu.ifi.dbs.elki.result.outlier.OutlierResult;
import de.lmu.ifi.dbs.elki.utilities.exceptions.AbortException;
/**
* This is a pseudo outlier scoring obtained by only considering the ranks of
* the objects. However, the ranks are not mapped linearly to scores, but using
* a normal distribution.
*
* @author Erich Schubert
*/
public class RankingPseudoOutlierScaling implements OutlierScalingFunction {
/**
* The actual scores
*/
private double[] scores;
/**
* Use inverted ranking
*/
private boolean inverted = false;
@Override
public void prepare(OutlierResult or) {
// collect all outlier scores
scores = new double[or.getScores().size()];
int pos = 0;
if(or.getOutlierMeta() instanceof InvertedOutlierScoreMeta) {
inverted = true;
}
for(DBID id : or.getScores().iterDBIDs()) {
scores[pos] = or.getScores().get(id);
pos++;
}
if(pos != or.getScores().size()) {
throw new AbortException("Database size is incorrect!");
}
// sort them
// TODO: Inverted scores!
Arrays.sort(scores);
}
@Override
public double getMax() {
return 1.0;
}
@Override
public double getMin() {
return 0.0;
}
@Override
public double getScaled(double value) {
assert (scores != null) : "prepare() was not run prior to using the scaling function.";
int pos = Arrays.binarySearch(scores, value);
if(inverted) {
return 1.0 - ((double) pos) / scores.length;
}
else {
return ((double) pos) / scores.length;
}
}
}
|
