#include <gpRegression.hpp>
Public Member Functions | |
void | buildGP (bool useTargets=true) |
void | buildTargets () |
void | evalGP (const TInput &x, double &mean, double &var) |
void | evalGP (const TInput &x, double &mean) |
double | getAvgVariance () |
double | getComplexity () |
double | getDataFit () |
double | getDataLikelihood () |
void | getDerivative (std::vector< double > *r) |
double | getMarginalDataLikelihood () |
void | getParameters (std::vector< double > *r) |
GPReg (CovFunc< TInput > *covFunc, double sigmaNoise, GPReg< TInput > *noiseGP=NULL) | |
GPReg (CovFunc< TInput > *covFunc, double *sigmaNoise, GPReg< TInput > *noiseGP=NULL) | |
GPReg (GPReg< TInput > *copyFromGP) | |
bool | minimizeGSL (unsigned maxIt) |
void | setDataPoints (TVector< TInput > &dataPoints, TVector< double > &dataTargets) |
void | setParameters (std::vector< double > *r) |
void | setSigmaNoise (double sigma) |
~GPReg () | |
Static Public Member Functions | |
static void | gsl_my_df (const gsl_vector *v, void *params, gsl_vector *df) |
static double | gsl_my_f (const gsl_vector *v, void *params) |
static void | gsl_my_fdf (const gsl_vector *v, void *params, double *f, gsl_vector *df) |
Public Attributes | |
TMatrix< double > * | m_C |
GPReg< TInput > * | m_copyFromGP |
CovFunc< TInput > * | m_covFunc |
TVector< TInput > * | m_dataPoints |
TMatrix< double > * | m_iC |
TVector< double > * | m_iCt |
GPReg< TInput > * | m_noiseGP |
int | m_numDataPoints |
double | m_ownSigmaNoise |
double * | m_sigmaNoise |
TVector< double > * | m_t |
Definition at line 18 of file gpRegression.hpp.
GPReg< TInput >::GPReg | ( | CovFunc< TInput > * | covFunc, |
double | sigmaNoise, | ||
GPReg< TInput > * | noiseGP = NULL |
||
) |
GPReg< TInput >::GPReg | ( | CovFunc< TInput > * | covFunc, |
double * | sigmaNoise, | ||
GPReg< TInput > * | noiseGP = NULL |
||
) |
void GPReg< TInput >::buildTargets | ( | ) |
void GPReg< TInput >::evalGP | ( | const TInput & | x, |
double & | mean, | ||
double & | var | ||
) |
double GPReg< TInput >::getAvgVariance | ( | ) |
double GPReg< TInput >::getComplexity | ( | ) |
double GPReg< TInput >::getDataFit | ( | ) |
double GPReg< TInput >::getDataLikelihood | ( | ) |
void GPReg< TInput >::getDerivative | ( | std::vector< double > * | r | ) |
double GPReg< TInput >::getMarginalDataLikelihood | ( | ) |
void GPReg< TInput >::getParameters | ( | std::vector< double > * | r | ) |
static void GPReg< TInput >::gsl_my_df | ( | const gsl_vector * | v, |
void * | params, | ||
gsl_vector * | df | ||
) | [static] |
static double GPReg< TInput >::gsl_my_f | ( | const gsl_vector * | v, |
void * | params | ||
) | [static] |
static void GPReg< TInput >::gsl_my_fdf | ( | const gsl_vector * | v, |
void * | params, | ||
double * | f, | ||
gsl_vector * | df | ||
) | [static] |
bool GPReg< TInput >::minimizeGSL | ( | unsigned | maxIt | ) |
void GPReg< TInput >::setDataPoints | ( | TVector< TInput > & | dataPoints, |
TVector< double > & | dataTargets | ||
) |
void GPReg< TInput >::setParameters | ( | std::vector< double > * | r | ) |
void GPReg< TInput >::setSigmaNoise | ( | double | sigma | ) |
Definition at line 58 of file gpRegression.hpp.
GPReg<TInput>* GPReg< TInput >::m_copyFromGP |
Definition at line 52 of file gpRegression.hpp.
Definition at line 62 of file gpRegression.hpp.
TVector<TInput>* GPReg< TInput >::m_dataPoints |
Definition at line 56 of file gpRegression.hpp.
Definition at line 60 of file gpRegression.hpp.
Definition at line 61 of file gpRegression.hpp.
Definition at line 66 of file gpRegression.hpp.
int GPReg< TInput >::m_numDataPoints |
Definition at line 54 of file gpRegression.hpp.
double GPReg< TInput >::m_ownSigmaNoise |
Definition at line 64 of file gpRegression.hpp.
double* GPReg< TInput >::m_sigmaNoise |
Definition at line 63 of file gpRegression.hpp.
Definition at line 57 of file gpRegression.hpp.