XMM - Probabilistic Models for Motion Recognition and Mapping

xmmKMeansResults.hpp
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1 /*
2  * xmmKMeansResults.hpp
3  *
4  * Results of the K-Means clustering Algorithm
5  *
6  * Contact:
7  * - Jules Francoise <jules.francoise@ircam.fr>
8  *
9  * This code has been initially authored by Jules Francoise
10  * <http://julesfrancoise.com> during his PhD thesis, supervised by Frederic
11  * Bevilacqua <href="http://frederic-bevilacqua.net>, in the Sound Music
12  * Movement Interaction team <http://ismm.ircam.fr> of the
13  * STMS Lab - IRCAM, CNRS, UPMC (2011-2015).
14  *
15  * Copyright (C) 2015 UPMC, Ircam-Centre Pompidou.
16  *
17  * This File is part of XMM.
18  *
19  * XMM is free software: you can redistribute it and/or modify
20  * it under the terms of the GNU General Public License as published by
21  * the Free Software Foundation, either version 3 of the License, or
22  * (at your option) any later version.
23  *
24  * XMM is distributed in the hope that it will be useful,
25  * but WITHOUT ANY WARRANTY; without even the implied warranty of
26  * MERCHANTABILITY or FITNESS FOR A PARTICULAR PURPOSE. See the
27  * GNU General Public License for more details.
28  *
29  * You should have received a copy of the GNU General Public License
30  * along with XMM. If not, see <http://www.gnu.org/licenses/>.
31  */
32 
33 #ifndef xmmKMeansResults_h
34 #define xmmKMeansResults_h
35 
36 #include "../../core/model/xmmModelResults.hpp"
37 
38 namespace xmm {
43 template <>
44 struct Results<KMeans> {
48  std::vector<float> distances;
49 
53  unsigned int likeliest;
54 };
55 }
56 
57 #endif
Results of the filtering/inference process (for a Model with multiple classes).
Definition: xmmModelResults.hpp:80
std::vector< float > distances
Distance of the observation to each cluster.
Definition: xmmKMeansResults.hpp:48
K-Means Clustering algorithm.
Definition: xmmKMeans.hpp:46
unsigned int likeliest
Likeliest Cluster.
Definition: xmmKMeansResults.hpp:53
Definition: xmmAttribute.hpp:42