HardClusteringModel.h
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1 //===========================================================================
2 /*!
3  *
4  *
5  * \brief Model for "hard" clustering.
6  *
7  *
8  *
9  * \author T. Glasmachers
10  * \date 2011
11  *
12  *
13  * \par Copyright 1995-2017 Shark Development Team
14  *
15  * <BR><HR>
16  * This file is part of Shark.
17  * <http://shark-ml.org/>
18  *
19  * Shark is free software: you can redistribute it and/or modify
20  * it under the terms of the GNU Lesser General Public License as published
21  * by the Free Software Foundation, either version 3 of the License, or
22  * (at your option) any later version.
23  *
24  * Shark 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 Lesser General Public License for more details.
28  *
29  * You should have received a copy of the GNU Lesser General Public License
30  * along with Shark. If not, see <http://www.gnu.org/licenses/>.
31  *
32  */
33 //===========================================================================
34 
35 #ifndef SHARK_MODELS_CLUSTERING_HARDCLUSTERINGMODEL_H
36 #define SHARK_MODELS_CLUSTERING_HARDCLUSTERINGMODEL_H
37 
39 
40 namespace shark {
41 
42 
43 ///
44 /// \brief Model for "hard" clustering.
45 ///
46 /// \par
47 /// The HardClusteringModel is based on an AbstractClustering
48 /// object. Given an input, the model outputs the index of the
49 /// best matching cluster.
50 ///
51 /// \par
52 /// See also SoftClusteringModel for general cluster membership.
53 ///
54 template <class InputT>
55 class HardClusteringModel : public ClusteringModel<InputT, unsigned int>
56 {
59 public:
62  typedef typename base_type::InputType InputType;
64 
65 
66  /// Constructor
67  HardClusteringModel(ClusteringType* clustering)
68  : base_type(clustering){
69  }
70 
71  /// \brief From INameable: return the class name.
72  std::string name() const
73  { return "HardClusteringModel"; }
74 
76 
77  Shape inputShape()const{
78  return this->mep_clustering->inputShape();
79  }
81  return this->mep_clustering->numberOfClusters();
82  }
83 
84  /// \brief Compute best matching cluster.
85  ///
86  /// \par
87  /// The actual computation is redirected to the clustering object.
88  void eval(InputType const & pattern, OutputType& output)const{
89  output = this->mep_clustering->hardMembership(pattern);
90  }
91 
92  /// \brief Compute best matching cluster for a batch of inputs.
93  ///
94  /// \par
95  /// The actual computation is redirected to the clustering object.
96  void eval(BatchInputType const & patterns, BatchOutputType& outputs)const{
97  outputs = this->mep_clustering->hardMembership(patterns);
98  }
99 };
100 
101 
102 }
103 #endif