Shark machine learning library
Installation
Tutorials
Benchmarks
Documentation
Quick references
Class list
Global functions
include
shark
Unsupervised
RBM
BinaryRBM.h
Go to the documentation of this file.
1
/*!
2
*
3
*
4
* \brief Typedefs for the Binary-Binary RBM.
5
*
6
* \author Oswin Krause Asja Fischer
7
* \date 1.2014
8
*
9
*
10
* \par Copyright 1995-2017 Shark Development Team
11
*
12
* <BR><HR>
13
* This file is part of Shark.
14
* <https://shark-ml.github.io/Shark/>
15
*
16
* Shark is free software: you can redistribute it and/or modify
17
* it under the terms of the GNU Lesser General Public License as published
18
* by the Free Software Foundation, either version 3 of the License, or
19
* (at your option) any later version.
20
*
21
* Shark is distributed in the hope that it will be useful,
22
* but WITHOUT ANY WARRANTY; without even the implied warranty of
23
* MERCHANTABILITY or FITNESS FOR A PARTICULAR PURPOSE. See the
24
* GNU Lesser General Public License for more details.
25
*
26
* You should have received a copy of the GNU Lesser General Public License
27
* along with Shark. If not, see <http://www.gnu.org/licenses/>.
28
*
29
*/
30
#ifndef SHARK_UNSUPERVISED_RBM_BINARYRBM_H
31
#define SHARK_UNSUPERVISED_RBM_BINARYRBM_H
32
33
#include <
shark/Unsupervised/RBM/RBM.h
>
34
#include <
shark/Unsupervised/RBM/Energy.h
>
35
36
#include <
shark/Unsupervised/RBM/Neuronlayers/BinaryLayer.h
>
37
#include <
shark/Unsupervised/RBM/Sampling/GibbsOperator.h
>
38
#include <
shark/Unsupervised/RBM/Sampling/TemperedMarkovChain.h
>
39
#include <
shark/Unsupervised/RBM/Sampling/MarkovChain.h
>
40
41
#include <
shark/Unsupervised/RBM/GradientApproximations/ContrastiveDivergence.h
>
42
#include <
shark/Unsupervised/RBM/GradientApproximations/MultiChainApproximator.h
>
43
#include <
shark/Unsupervised/RBM/GradientApproximations/SingleChainApproximator.h
>
44
#include <
shark/Core/Random.h
>
45
namespace
shark
{
46
47
typedef
RBM<BinaryLayer,BinaryLayer, random::rng_type>
BinaryRBM
;
48
typedef
GibbsOperator<BinaryRBM>
BinaryGibbsOperator
;
49
typedef
MarkovChain<BinaryGibbsOperator>
BinaryGibbsChain
;
50
typedef
TemperedMarkovChain<BinaryGibbsOperator>
BinaryPTChain
;
51
52
typedef
MultiChainApproximator<BinaryGibbsChain>
BinaryPCD
;
53
typedef
ContrastiveDivergence<BinaryGibbsOperator>
BinaryCD
;
54
typedef
SingleChainApproximator<BinaryPTChain>
BinaryParallelTempering
;
55
}
56
57
#endif