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SingleFITCLaplacianBase.h
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31 
32 #ifndef CSINGLEFITCLAPLACIANBASE_H
33 #define CSINGLEFITCLAPLACIANBASE_H
34 
35 #include <shogun/lib/config.h>
36 
37 #ifdef HAVE_EIGEN3
38 
40 #include <shogun/lib/Lock.h>
41 
42 namespace shogun
43 {
44 
71 {
72 public:
75 
85  CSingleFITCLaplacianBase(CKernel* kernel, CFeatures* features,
86  CMeanFunction* mean, CLabels* labels, CLikelihoodModel* model,
87  CFeatures* inducing_features);
88 
89  virtual ~CSingleFITCLaplacianBase();
90 
95  virtual const char* get_name() const { return "SingleFITCLaplacianBase"; }
96 
97 protected:
98 
114 
133 
150 
158  const TParameter* param);
159 
166 
174 
185  SGMatrix<float64_t> BdK, const TParameter* param);
186 
188  virtual void update_alpha()=0;
189 
191  virtual void update_chol()=0;
192 
196  virtual void update_deriv()=0;
197 
206  const TParameter* param)=0;
207 
216  const TParameter* param);
217 
228 
233 
239 
240  /* B is defined in infFITC.m and infFITC_Laplace.m */
242 
243  /* w=B*al */
245 
251 
252  /* V defined in infFITC.m and infFITC_Laplace.m */
254 
255 private:
256  /* init */
257  void init();
258 };
259 }
260 #endif /* HAVE_EIGEN3 */
261 #endif /* CSINGLEFITCLAPLACIANBASE_H */
The class Labels models labels, i.e. class assignments of objects.
Definition: Labels.h:43
virtual SGVector< float64_t > get_derivative_wrt_mean(const TParameter *param)
parameter struct
An abstract class of the mean function.
Definition: MeanFunction.h:49
virtual SGVector< float64_t > get_derivative_wrt_inducing_noise(const TParameter *param)
The Fully Independent Conditional Training inference base class for Laplace and regression for 1-D la...
virtual float64_t get_derivative_related_cov(SGVector< float64_t > ddiagKi, SGMatrix< float64_t > dKuui, SGMatrix< float64_t > dKui)
virtual const char * get_name() const
double float64_t
Definition: common.h:50
virtual SGVector< float64_t > get_derivative_wrt_likelihood_model(const TParameter *param)=0
virtual SGVector< float64_t > get_derivative_related_cov_diagonal()
The sparse inference base class for classification and regression for 1-D labels (1D regression and b...
virtual SGVector< float64_t > get_derivative_related_inducing_features(SGMatrix< float64_t > BdK, const TParameter *param)
virtual float64_t get_derivative_related_mean(SGVector< float64_t > dmu)
all of classes and functions are contained in the shogun namespace
Definition: class_list.h:18
The class Features is the base class of all feature objects.
Definition: Features.h:68
The Kernel base class.
Definition: Kernel.h:158
virtual SGVector< float64_t > get_derivative_wrt_inducing_features(const TParameter *param)
The Likelihood model base class.
virtual float64_t get_derivative_related_cov_helper(SGMatrix< float64_t > dKuui, SGVector< float64_t > v, SGMatrix< float64_t > R)

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