13#include <MachineLearning/FgIBackconstraint.h>
14#include <MachineLearning/FgKernels.h>
18 namespace MachineLearning
66 template<
typename Scalar>
93 virtual void Init(
const af::array& Y,
const af::array& X,
const af::array& segments);
167 friend class boost::serialization::access;
169 template<
class Archive>
170 void serialize(Archive& ar,
unsigned int version)
172 ar& boost::serialization::base_object<IBackconstraint<Scalar>>(*this);
174 ar& BOOST_SERIALIZATION_NVP(afA);
175 ar& BOOST_SERIALIZATION_NVP(afK);
176 ar& BOOST_SERIALIZATION_NVP(kernel);
Abstract class for back-constraints, a kind of prior knowledge to force topological positions of unce...
Back-constraints via kernel based regression.
virtual void SetParameters(const af::array ¶m)
Sets the parameters.
IKernel< Scalar > * kernel
kernel function
KBR()
Default constructor.
virtual af::array GetParameters()
Gets the parameters.
virtual int GetNumParameters()
Gets number of to be optimized parameters.
virtual void Init(const af::array &Y, const af::array &X, const af::array &segments)
Initializes this object.
virtual IKernel< Scalar > * GetKernel()
Gets the kernel function.
virtual af::array GetConstraintX()
Gets constraint x coordinates.
virtual ~KBR()
Destructor.
virtual af::array BackconstraintGradient(const af::array &gX)
Back-constraint gradient.
af::array afK
kernel matrix
virtual void SetKernel(IKernel< Scalar > *inKernel)
Sets a kernel function.