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AveragedPerceptron.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) 2011 Hidekazu Oiwa
8  */
9 
10 #ifndef _AVERAGEDPERCEPTRON_H___
11 #define _AVERAGEDPERCEPTRON_H___
12 
13 #include <stdio.h>
14 #include <shogun/lib/common.h>
17 
18 namespace shogun
19 {
31 {
32  public:
35 
41  CAveragedPerceptron(CDotFeatures* traindat, CLabels* trainlab);
42  virtual ~CAveragedPerceptron();
43 
49 
58  virtual bool train(CFeatures* data=NULL);
59 
61  inline void set_learn_rate(float64_t r)
62  {
63  learn_rate=r;
64  }
65 
67  inline void set_max_iter(int32_t i)
68  {
69  max_iter=i;
70  }
71 
73  inline virtual const char* get_name() const { return "AveragedPerceptron"; }
74 
75  protected:
79  int32_t max_iter;
80 };
81 }
82 #endif
virtual const char * get_name() const
EClassifierType
Definition: Machine.h:27
The class Labels models labels, i.e. class assignments of objects.
Definition: Labels.h:35
void set_learn_rate(float64_t r)
set learn rate of gradient descent training algorithm
Class Averaged Perceptron implements the standard linear (online) algorithm. Averaged perceptron is t...
Features that support dot products among other operations.
Definition: DotFeatures.h:41
double float64_t
Definition: common.h:56
Class LinearMachine is a generic interface for all kinds of linear machines like classifiers.
Definition: LinearMachine.h:61
The class Features is the base class of all feature objects.
Definition: Features.h:56
virtual EClassifierType get_classifier_type()
virtual bool train(CFeatures *data=NULL)
void set_max_iter(int32_t i)
set maximum number of iterations

SHOGUN Machine Learning Toolbox - Documentation