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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 
38 
44  CAveragedPerceptron(CDotFeatures* traindat, CLabels* trainlab);
45  virtual ~CAveragedPerceptron();
46 
52 
54  inline void set_learn_rate(float64_t r)
55  {
56  learn_rate=r;
57  }
58 
60  inline void set_max_iter(int32_t i)
61  {
62  max_iter=i;
63  }
64 
66  virtual const char* get_name() const { return "AveragedPerceptron"; }
67 
68 protected:
69 
78  virtual bool train_machine(CFeatures* data=NULL);
79 
80  protected:
84  int32_t max_iter;
85 };
86 }
87 #endif
EMachineType
Definition: Machine.h:33
virtual const char * get_name() const
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...
virtual EMachineType get_classifier_type()
Features that support dot products among other operations.
Definition: DotFeatures.h:41
double float64_t
Definition: common.h:48
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:62
virtual bool train_machine(CFeatures *data=NULL)
void set_max_iter(int32_t i)
set maximum number of iterations

SHOGUN Machine Learning Toolbox - Documentation