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Machine.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) 1999-2009 Soeren Sonnenburg
8  * Written (W) 2011-2012 Heiko Strathmann
9  * Copyright (C) 1999-2009 Fraunhofer Institute FIRST and Max-Planck-Society
10  */
11 
12 #ifndef _MACHINE_H__
13 #define _MACHINE_H__
14 
15 #include <shogun/lib/config.h>
16 
17 #include <shogun/lib/common.h>
18 #include <shogun/base/SGObject.h>
25 
26 namespace shogun
27 {
28 
29 class CFeatures;
30 class CLabels;
31 
34 {
35  CT_NONE = 0,
36  CT_LIGHT = 10,
38  CT_LIBSVM = 20,
41  CT_MPD = 50,
42  CT_GPBT = 60,
46  CT_LDA = 100,
47  CT_LPM = 110,
48  CT_LPBOOST = 120,
49  CT_KNN = 130,
50  CT_SVMLIN=140,
52  CT_GNPPSVM = 160,
53  CT_GMNPSVM = 170,
54  CT_SVMPERF = 200,
55  CT_LIBSVR = 210,
56  CT_SVRLIGHT = 220,
57  CT_LIBLINEAR = 230,
58  CT_KMEANS = 240,
60  CT_SVMOCAS = 260,
61  CT_WDSVMOCAS = 270,
62  CT_SVMSGD = 280,
68  CT_DASVM = 340,
69  CT_LARANK = 350,
73  CT_SGDQN = 390,
77  CT_QDA = 430,
78  CT_NEWTONSVM = 440,
80  CT_LARS = 460,
86  CT_CCSOSVM = 520,
92 };
93 
96 {
104 };
105 
108 {
114 };
115 
116 #define MACHINE_PROBLEM_TYPE(PT) \
117  \
120  virtual EProblemType get_machine_problem_type() const { return PT; }
121 
139 class CMachine : public CSGObject
140 {
141  public:
143  CMachine();
144 
146  virtual ~CMachine();
147 
157  virtual bool train(CFeatures* data=NULL);
158 
165  virtual CLabels* apply(CFeatures* data=NULL);
166 
168  virtual CBinaryLabels* apply_binary(CFeatures* data=NULL);
170  virtual CRegressionLabels* apply_regression(CFeatures* data=NULL);
172  virtual CMulticlassLabels* apply_multiclass(CFeatures* data=NULL);
174  virtual CStructuredLabels* apply_structured(CFeatures* data=NULL);
176  virtual CLatentLabels* apply_latent(CFeatures* data=NULL);
177 
182  virtual void set_labels(CLabels* lab);
183 
188  virtual CLabels* get_labels();
189 
195 
201 
207 
212  void set_solver_type(ESolverType st);
213 
219 
225  virtual void set_store_model_features(bool store_model);
226 
235  virtual bool train_locked(SGVector<index_t> indices)
236  {
237  SG_ERROR("train_locked(SGVector<index_t>) is not yet implemented "
238  "for %s\n", get_name());
239  return false;
240  }
243  virtual float64_t apply_one(int32_t i)
244  {
246  return 0.0;
247  }
248 
254  virtual CLabels* apply_locked(SGVector<index_t> indices);
255 
258  SGVector<index_t> indices);
261  SGVector<index_t> indices);
264  SGVector<index_t> indices);
267  SGVector<index_t> indices);
270  SGVector<index_t> indices);
271 
280  virtual void data_lock(CLabels* labs, CFeatures* features);
283  virtual void post_lock(CLabels* labs, CFeatures* features) { };
284 
286  virtual void data_unlock();
289  virtual bool supports_locking() const { return false; }
292  bool is_data_locked() const { return m_data_locked; }
295  virtual EProblemType get_machine_problem_type() const
296  {
298  return PT_BINARY;
299  }
300 
301  virtual const char* get_name() const { return "Machine"; }
302 
303  protected:
314  virtual bool train_machine(CFeatures* data=NULL)
315  {
316  SG_ERROR("train_machine is not yet implemented for %s!\n",
317  get_name());
318  return false;
319  }
320 
331  virtual void store_model_features()
332  {
333  SG_ERROR("Model storage and therefore unlocked Cross-Validation and"
334  " Model-Selection is not supported for %s. Locked may"
335  " work though.\n", get_name());
336  }
337 
344  virtual bool is_label_valid(CLabels *lab) const
345  {
346  return true;
347  }
350  virtual bool train_require_labels() const { return true; }
351 
352  protected:
357  CLabels* m_labels;
366  bool m_data_locked;
367 };
368 }
369 #endif // _MACHINE_H__

SHOGUN Machine Learning Toolbox - Documentation