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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/common.h>
16 #include <shogun/base/SGObject.h>
17 #include <shogun/labels/Labels.h>
24 
25 namespace shogun
26 {
27 
28 class CFeatures;
29 class CLabels;
30 class CMath;
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,
91 };
92 
95 {
103 };
104 
107 {
113 };
114 
115 #define MACHINE_PROBLEM_TYPE(PT) \
116  \
119  virtual EProblemType get_machine_problem_type() const { return PT; }
120 
138 class CMachine : public CSGObject
139 {
140  public:
142  CMachine();
143 
145  virtual ~CMachine();
146 
156  virtual bool train(CFeatures* data=NULL);
157 
164  virtual CLabels* apply(CFeatures* data=NULL);
165 
167  virtual CBinaryLabels* apply_binary(CFeatures* data=NULL);
169  virtual CRegressionLabels* apply_regression(CFeatures* data=NULL);
171  virtual CMulticlassLabels* apply_multiclass(CFeatures* data=NULL);
173  virtual CStructuredLabels* apply_structured(CFeatures* data=NULL);
175  virtual CLatentLabels* apply_latent(CFeatures* data=NULL);
176 
181  virtual void set_labels(CLabels* lab);
182 
187  virtual CLabels* get_labels();
188 
194 
200 
206 
211  void set_solver_type(ESolverType st);
212 
218 
224  virtual void set_store_model_features(bool store_model);
225 
234  virtual bool train_locked(SGVector<index_t> indices)
235  {
236  SG_ERROR("train_locked(SGVector<index_t>) is not yet implemented "
237  "for %s\n", get_name());
238  return false;
239  }
240 
242  virtual float64_t apply_one(int32_t i)
243  {
245  return 0.0;
246  }
247 
253  virtual CLabels* apply_locked(SGVector<index_t> indices);
254 
257  SGVector<index_t> indices);
260  SGVector<index_t> indices);
263  SGVector<index_t> indices);
266  SGVector<index_t> indices);
269  SGVector<index_t> indices);
270 
279  virtual void data_lock(CLabels* labs, CFeatures* features);
280 
282  virtual void post_lock(CLabels* labs, CFeatures* features) { };
283 
285  virtual void data_unlock();
286 
288  virtual bool supports_locking() const { return false; }
289 
291  bool is_data_locked() const { return m_data_locked; }
292 
295  {
297  return PT_BINARY;
298  }
299 
300  virtual const char* get_name() const { return "Machine"; }
301 
302  protected:
313  virtual bool train_machine(CFeatures* data=NULL)
314  {
315  SG_ERROR("train_machine is not yet implemented for %s!\n",
316  get_name());
317  return false;
318  }
319 
330  virtual void store_model_features()
331  {
332  SG_ERROR("Model storage and therefore unlocked Cross-Validation and"
333  " Model-Selection is not supported for %s. Locked may"
334  " work though.\n", get_name());
335  }
336 
343  virtual bool is_label_valid(CLabels *lab) const
344  {
345  return true;
346  }
347 
349  virtual bool train_require_labels() const { return true; }
350 
351  protected:
354 
357 
360 
363 
366 };
367 }
368 #endif // _MACHINE_H__

SHOGUN Machine Learning Toolbox - Documentation