NormalizeComponentsWhitening.h
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1 //===========================================================================
2 /*!
3  *
4  *
5  * \brief Data normalization to zero mean, unit variance and zero covariance
6  *
7  *
8  *
9  *
10  * \author T. Glasmachers,O.Krause
11  * \date 2016
12  *
13  *
14  * \par Copyright 1995-2017 Shark Development Team
15  *
16  * <BR><HR>
17  * This file is part of Shark.
18  * <http://shark-ml.org/>
19  *
20  * Shark is free software: you can redistribute it and/or modify
21  * it under the terms of the GNU Lesser General Public License as published
22  * by the Free Software Foundation, either version 3 of the License, or
23  * (at your option) any later version.
24  *
25  * Shark is distributed in the hope that it will be useful,
26  * but WITHOUT ANY WARRANTY; without even the implied warranty of
27  * MERCHANTABILITY or FITNESS FOR A PARTICULAR PURPOSE. See the
28  * GNU Lesser General Public License for more details.
29  *
30  * You should have received a copy of the GNU Lesser General Public License
31  * along with Shark. If not, see <http://www.gnu.org/licenses/>.
32  *
33  */
34 //===========================================================================
35 
36 
37 #ifndef SHARK_ALGORITHMS_TRAINERS_NORMALIZECOMPONENTSWHITENING_H
38 #define SHARK_ALGORITHMS_TRAINERS_NORMALIZECOMPONENTSWHITENING_H
39 
40 #include <shark/Core/DLLSupport.h>
41 #include <shark/Models/LinearModel.h>
42 #include <shark/Algorithms/Trainers/AbstractTrainer.h>
43 
44 namespace shark {
45 
46 
47 /// \brief Train a linear model to whiten the data.
48 ///
49 /// computes a linear model that normlizes the data to be 0 mean, a given target variance and covariance 0.
50 /// By default the trainer makes the data unit variance, but the target variance can be changed as well.
51 class NormalizeComponentsWhitening : public AbstractUnsupervisedTrainer<LinearModel<RealVector> >
52 {
53 public:
54  SHARK_EXPORT_SYMBOL NormalizeComponentsWhitening(double targetVariance = 1.0);
55 
56  /// \brief From INameable: return the class name.
57  SHARK_EXPORT_SYMBOL std::string name() const;
58 
59  SHARK_EXPORT_SYMBOL void train(ModelType& model, UnlabeledData<RealVector> const& input);
60 
61 private:
62  double m_targetVariance;
63 };
64 
65 
66 }
67 #endif