15 #ifndef CFITCINFERENCEMETHOD_H_
16 #define CFITCINFERENCEMETHOD_H_
71 virtual const char*
get_name()
const {
return "FITCInferenceMethod"; }
88 m_latent_features=feat;
98 return m_latent_features;
virtual EInferenceType get_inference_type() const
virtual void update_alpha()
virtual SGVector< float64_t > get_derivative_wrt_inference_method(const TParameter *param)
virtual CFeatures * get_latent_features()
The Inference Method base class.
virtual void update_chol()
virtual SGVector< float64_t > get_diagonal_vector()
The class Labels models labels, i.e. class assignments of objects.
virtual void update_train_kernel()
virtual ~CFITCInferenceMethod()
virtual const char * get_name() const
virtual SGMatrix< float64_t > get_cholesky()
virtual SGVector< float64_t > get_posterior_mean()
An abstract class of the mean function.
virtual float64_t get_negative_log_marginal_likelihood()
virtual void check_members() const
virtual SGVector< float64_t > get_derivative_wrt_kernel(const TParameter *param)
virtual bool supports_regression() const
virtual bool supports_regression() const
The class Features is the base class of all feature objects.
The Fully Independent Conditional Training inference method class.
virtual SGVector< float64_t > get_derivative_wrt_likelihood_model(const TParameter *param)
virtual void set_latent_features(CFeatures *feat)
virtual void update_deriv()
virtual SGVector< float64_t > get_derivative_wrt_mean(const TParameter *param)
virtual SGVector< float64_t > get_alpha()
The Likelihood model base class.
CLikelihoodModel * m_model
virtual SGMatrix< float64_t > get_posterior_covariance()
static CFITCInferenceMethod * obtain_from_generic(CInferenceMethod *inference)