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FirstOrderMinimizer.h
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1 /*
2  * Copyright (c) The Shogun Machine Learning Toolbox
3  * Written (w) 2015 Wu Lin
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31 
32 #ifndef FIRSTORDERMINIMIZER_H
33 #define FIRSTORDERMINIMIZER_H
34 #include <shogun/lib/config.h>
38 namespace shogun
39 {
40 
55 {
56 public:
59  {
60  init();
61  }
62 
67  {
68  init();
69  set_cost_function(fun);
70  }
71 
74  {}
75 
80  virtual float64_t minimize()=0;
81 
86  virtual bool supports_batch_update() const=0;
87 
93  {
94  REQUIRE(fun,"The cost function must be not NULL\n");
95  m_fun=fun;
96  }
97 
104  {
105  CMinimizerContext* result=new CMinimizerContext();
106  update_context(result);
107  return result;
108  }
109 
115  virtual void load_from_context(CMinimizerContext* context)
116  {
117  REQUIRE(context,"Context must set\n");
118  if(m_penalty_type)
120  }
121 
126  virtual void set_penalty_weight(float64_t penalty_weight)
127  {
128  REQUIRE(penalty_weight>0,"The weight of penalty must be positive\n");
129  m_penalty_weight=penalty_weight;
130  }
131 
137  virtual void set_penalty_type(Penalty* penalty_type)
138  {
139  m_penalty_type=penalty_type;
140  }
141 protected:
142 
147  virtual void update_context(CMinimizerContext* context)
148  {
149  REQUIRE(context,"Context must set\n");
150  if(m_penalty_type)
151  m_penalty_type->update_context(context);
152  }
153 
165  {
166  float64_t penalty=0.0;
167  if(m_penalty_type)
168  {
169  REQUIRE(m_penalty_weight>0,"The weight of penalty must be set first\n");
170  for(index_t idx=0; idx<var.vlen; idx++)
171  penalty+=m_penalty_weight*m_penalty_type->get_penalty(var[idx]);
172  }
173  return penalty;
174  }
175 
191  {
192  if(m_penalty_type)
193  {
194  REQUIRE(m_penalty_weight>0,"The weight of penalty must be set first\n");
195  for(index_t idx=0; idx<var.vlen; idx++)
196  {
197  float64_t grad=gradient[idx];
198  float64_t variable=var[idx];
199  gradient[idx]+=m_penalty_weight*m_penalty_type->get_penalty_gradient(variable,grad);
200  }
201  }
202  }
203 
206 
209 
212 
213 private:
215  void init()
216  {
217  m_fun=NULL;
218  m_penalty_type=NULL;
219  m_penalty_weight=0;
220  }
221 };
222 
223 }
224 #endif
virtual float64_t get_penalty_gradient(float64_t variable, float64_t gradient)=0
virtual void update_gradient(SGVector< float64_t > gradient, SGVector< float64_t > var)
int32_t index_t
Definition: common.h:62
The class is used to serialize and deserialize variables for the optimization framework.
virtual void set_penalty_weight(float64_t penalty_weight)
FirstOrderCostFunction * m_fun
#define REQUIRE(x,...)
Definition: SGIO.h:206
The base class for penalty/regularization used in minimization.
Definition: Penalty.h:46
index_t vlen
Definition: SGVector.h:494
virtual void set_cost_function(FirstOrderCostFunction *fun)
virtual float64_t get_penalty(float64_t variable)=0
double float64_t
Definition: common.h:50
virtual CMinimizerContext * save_to_context()
virtual void update_context(CMinimizerContext *context)=0
FirstOrderMinimizer(FirstOrderCostFunction *fun)
virtual float64_t get_penalty(SGVector< float64_t > var)
The first order cost function base class.
virtual void load_from_context(CMinimizerContext *context)=0
virtual bool supports_batch_update() const =0
all of classes and functions are contained in the shogun namespace
Definition: class_list.h:18
virtual void load_from_context(CMinimizerContext *context)
virtual float64_t minimize()=0
virtual void set_penalty_type(Penalty *penalty_type)
virtual void update_context(CMinimizerContext *context)
The first order minimizer base class.

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