#include <KernelFunction.h>

Public Member Functions | |
| RBFKernel (double gamma) | |
| ~RBFKernel () | |
| double | eval (const Array< double > &x1, const Array< double > &x2) const |
| Evaluates the kernel function on a const object. | |
| double | evalDerivative (const Array< double > &x1, const Array< double > &x2, Array< double > &derivative) const |
| Evaluates the kernel function and computes its derivatives w.r.t. | |
| bool | isFeasible () |
| check whether the parameters define a feasible model | |
| double | getSigma () |
| void | setSigma (double sigma) |
A special but very important type of kernel is the Gaussian normal distribution density kernel
It has a single parameter
controlling the kernel width
.
CrossValidation.cpp, KernelOptimization.cpp, KM.cpp, KNN.cpp, McSvm.cpp, SvmApproximationExample.cpp, SVMclassification-gnuplot.cpp, SVMclassification.cpp, SVMregression-gnuplot.cpp, and SVMregression.cpp.
Definition at line 170 of file KernelFunction.h.
| RBFKernel::RBFKernel | ( | double | gamma | ) |
| RBFKernel::~RBFKernel | ( | ) |
Definition at line 188 of file KernelFunction.cpp.
| double RBFKernel::eval | ( | const Array< double > & | x1, | |
| const Array< double > & | x2 | |||
| ) | const [virtual] |
Evaluates the kernel function on a const object.
Implements KernelFunction.
Definition at line 193 of file KernelFunction.cpp.
References i, and Model::parameter.
| double RBFKernel::evalDerivative | ( | const Array< double > & | x1, | |
| const Array< double > & | x2, | |||
| Array< double > & | derivative | |||
| ) | const [virtual] |
Evaluates the kernel function and computes its derivatives w.r.t.
the kernel parameters.
Reimplemented from KernelFunction.
Definition at line 209 of file KernelFunction.cpp.
References i, and Model::parameter.
| double RBFKernel::getSigma | ( | ) |
| bool RBFKernel::isFeasible | ( | ) | [virtual] |
check whether the parameters define a feasible model
The default implementation returns true, that is, every parameter configuration is considered feasible and unconstrained optimization is applicable. It is the Optimizer's responsibility to check the isFeasible() flag.
Reimplemented from Model.
Definition at line 228 of file KernelFunction.cpp.
References Model::parameter.
| void RBFKernel::setSigma | ( | double | sigma | ) |