13#include <MachineLearning/FgSparseGPBaseModel.h>
17 namespace MachineLearning
49 template<
typename Scalar>
66 SGPR(
const af::array& Y,
const af::array& X,
int numInducing = 20,
Scalar alpha = 1.0, LogLikType lType = LogLikType::Gaussian);
78 virtual Scalar Function(
const af::array& x, af::array& outGradient)
override;
93 friend class boost::serialization::access;
95 template<
class Archive>
96 void serialize(Archive& ar,
unsigned int version)
98 ar& boost::serialization::base_object<SparseGPBaseModel<Scalar>>(*this);
100 ar& BOOST_SERIALIZATION_NVP(dAlpha);
Sparse Gaussian process via Approximated Expectation Propagation (AEP).
SGPR()
Default constructor.
virtual Scalar Function(const af::array &x, af::array &outGradient) override
Cost function the given parameter inputs.
Scalar dAlpha
fraction parameter
SGPR(const af::array &Y, const af::array &X, int numInducing=20, Scalar alpha=1.0, LogLikType lType=LogLikType::Gaussian)
Constructor.
Base class for all sparse GP models.