32 #ifndef CSINGLEFITCLAPLACEINFERENCEMETHOD_H 33 #define CSINGLEFITCLAPLACEINFERENCEMETHOD_H 36 #include <shogun/lib/config.h> 86 virtual const char*
get_name()
const {
return "SingleFITCLaplaceInferenceMethod"; }
397 virtual const char*
get_name()
const {
return "SingleFITCLaplaceNewtonOptimizer"; }
409 void unset_target(
bool is_unref);
SGVector< float64_t > m_dg
virtual void update_deriv()
SGVector< float64_t > m_dfhat
CSingleFITCLaplaceNewtonOptimizer()
virtual SGVector< float64_t > get_derivative_wrt_inducing_noise(const TParameter *param)
virtual void set_minimization_tolerance(float64_t tol)
friend class CFITCPsiLine
void get_gradient_wrt_alpha(SGVector< float64_t > gradient)
The class Labels models labels, i.e. class assignments of objects.
virtual void check_members() const
The build-in minimizer for SingleFITCLaplaceInference.
virtual void update_approx_cov()
virtual void update_alpha()
SGVector< float64_t > m_W
SGVector< float64_t > m_mean_f
virtual SGVector< float64_t > get_derivative_wrt_inference_method(const TParameter *param)
virtual bool supports_regression() const
virtual SGVector< float64_t > get_derivative_wrt_mean(const TParameter *param)
CSingleFITCLaplaceInferenceMethod()
virtual EInferenceType get_inference_type() const
static CSingleFITCLaplaceInferenceMethod * obtain_from_generic(CInference *inference)
SGVector< float64_t > m_d3lp
An abstract class of the mean function.
std::enable_if<!std::is_same< T, complex128_t >::value, float64_t >::type mean(const Container< T > &a)
SGVector< float64_t > m_g
virtual void update_init()
virtual void register_minimizer(Minimizer *minimizer)
SGVector< float64_t > m_d2lp
virtual const char * get_name() const
virtual bool supports_binary() const
SGVector< float64_t > m_sW
virtual SGVector< float64_t > get_diagonal_vector()
virtual bool supports_binary() const
SGMatrix< float64_t > m_chol_R0
virtual void set_newton_tolerance(float64_t tol)
friend class SingleFITCLaplaceInferenceMethodCostFunction
virtual float64_t get_negative_log_marginal_likelihood()
virtual SGVector< float64_t > derivative_helper_when_Wneg(SGVector< float64_t > res, const TParameter *param)
virtual ~CSingleFITCLaplaceNewtonOptimizer()
virtual SGVector< float64_t > get_posterior_mean()
virtual SGVector< float64_t > compute_mvmZ(SGVector< float64_t > x)
virtual void compute_gradient()
virtual void update_chol()
float64_t get_psi_wrt_alpha()
virtual void set_newton_iterations(int32_t iter)
all of classes and functions are contained in the shogun namespace
The Inference Method base class.
virtual SGMatrix< float64_t > get_posterior_covariance()
virtual float64_t get_derivative_implicit_term_helper(SGVector< float64_t > d)
SGVector< float64_t > m_dlp
The class Features is the base class of all feature objects.
virtual ~CSingleFITCLaplaceInferenceMethod()
virtual float64_t get_derivative_related_cov(SGVector< float64_t > ddiagKi, SGMatrix< float64_t > dKuui, SGMatrix< float64_t > dKui)
virtual SGVector< float64_t > compute_mvmK(SGVector< float64_t > al)
virtual bool supports_regression() const
virtual void set_minimization_max(float64_t max)
virtual const char * get_name() const
The minimizer base class.
virtual SGMatrix< float64_t > get_chol_inv(SGMatrix< float64_t > mtx)
The FITC approximation inference method class for regression and binary Classification. Note that the number of inducing points (m) is usually far less than the number of input points (n). (the time complexity is computed based on the assumption m < n)
The Fully Independent Conditional Training inference base class for Laplace and regression for 1-D la...
T max(const Container< T > &a)
virtual SGVector< float64_t > get_derivative_wrt_inducing_features(const TParameter *param)
CLikelihoodModel * m_model
virtual SGVector< float64_t > get_derivative_wrt_kernel(const TParameter *param)
The Likelihood model base class.
virtual float64_t get_derivative_related_mean(SGVector< float64_t > dmu)
virtual SGVector< float64_t > get_derivative_wrt_likelihood_model(const TParameter *param)