blob: b7bc1c67edac51dbda89d8e9ab0c5eb7292fc44c (
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
|
package de.lmu.ifi.dbs.elki.math.linearalgebra.pca.weightfunctions;
/*
This file is part of ELKI:
Environment for Developing KDD-Applications Supported by Index-Structures
Copyright (C) 2015
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 de.lmu.ifi.dbs.elki.math.statistics.distribution.NormalDistribution;
/**
* Gaussian Error Function Weight function, scaled such that the result it 0.1
* at distance == max
*
* erfc(1.1630871536766736 * distance / max)
*
* The value of 1.1630871536766736 is erfcinv(0.1), to achieve the intended
* scaling.
*
* @author Erich Schubert
*/
public final class ErfcWeight implements WeightFunction {
/**
* Get Erfc Weight, using distance / max. stddev is ignored.
*/
@Override
public double getWeight(double distance, double max, double stddev) {
if(max <= 0) {
return 1.0;
}
double relativedistance = distance / max;
// the scaling was picked such that getWeight(a,a,0) is 0.1
// since erfc(1.1630871536766736) == 1.0
return NormalDistribution.erfc(1.1630871536766736 * relativedistance);
}
}
|
