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LinearLatentMachine.h
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1 /*
2  * This program is free software; you can redistribute it and/or modify
3  * it under the terms of the GNU General Public License as published by
4  * the Free Software Foundation; either version 3 of the License, or
5  * (at your option) any later version.
6  *
7  * Written (W) 2012 Viktor Gal
8  * Copyright (C) 2012 Viktor Gal
9  */
10 
11 #ifndef __LATENTLINEARMACHINE_H__
12 #define __LATENTLINEARMACHINE_H__
13 
14 #include <shogun/lib/common.h>
17 
18 namespace shogun
19 {
24  {
25 
26  public:
27 
30 
33 
40 
41  virtual ~CLinearLatentMachine();
42 
47  virtual CLatentLabels* apply_latent() = 0;
48 
54  virtual CLatentLabels* apply_latent(CFeatures* data);
55 
60  virtual const char* get_name() const { return "LinearLatentMachine"; }
61 
66  inline void set_epsilon(float64_t eps) { m_epsilon=eps; }
67 
72  inline float64_t get_epsilon() { return m_epsilon; }
73 
78  inline void set_C(float64_t c)
79  {
80  m_C=c;
81  }
82 
87  inline float64_t get_C() { return m_C; }
88 
93  inline void set_max_iterations(int32_t iter) { m_max_iter = iter; }
94 
99  inline int32_t get_max_iterations() { return m_max_iter; }
100 
105  void set_model(CLatentModel* latent_model);
106 
107  protected:
108  virtual bool train_machine(CFeatures* data=NULL);
109 
116  virtual float64_t do_inner_loop(float64_t cooling_eps)=0;
117 
118  virtual bool train_require_labels() const { return false; }
119 
120  protected:
128  int32_t m_max_iter;
130  int32_t m_cur_iter;
131 
132  private:
134  void init();
135  };
136 }
137 
138 #endif /* __LATENTLINEARMACHINE_H__ */
139 
virtual float64_t do_inner_loop(float64_t cooling_eps)=0
Abstract class CLatentModel It represents the application specific model and contains most of the app...
Definition: LatentModel.h:31
virtual CLatentLabels * apply_latent()=0
virtual const char * get_name() const
virtual bool train_require_labels() const
double float64_t
Definition: common.h:48
void set_model(CLatentModel *latent_model)
void set_max_iterations(int32_t iter)
Class LinearMachine is a generic interface for all kinds of linear machines like classifiers.
Definition: LinearMachine.h:61
all of classes and functions are contained in the shogun namespace
Definition: class_list.h:16
abstract implementaion of Linear Machine with latent variable This is the base implementation of all ...
The class Features is the base class of all feature objects.
Definition: Features.h:62
virtual bool train_machine(CFeatures *data=NULL)
abstract class for latent labels As latent labels always depends on the given application, this class only defines the API that the user has to implement for latent labels.
Definition: LatentLabels.h:24

SHOGUN Machine Learning Toolbox - Documentation