An example kernel function. More...
Public Member Functions  
ExampleKernel ()  
The default constructor, which takes no parameters. More...  
template < typename Archive >  
void  serialize (Archive &, const unsigned int) 
Serializes the kernel. More...  
Static Public Member Functions  
template < typename VecTypeA , typename VecTypeB >  
static double  ConvolutionIntegral (const VecTypeA &, const VecTypeB &) 
Obtains the convolution integral [integral K(xa)K(bx)dx] for the two vectors. More...  
template < typename VecTypeA , typename VecTypeB >  
static double  Evaluate (const VecTypeA &, const VecTypeB &) 
Evaluates the kernel function for two given vectors. More...  
static double  Normalizer () 
Obtains the normalizing volume for the kernel with dimension $dimension$. More...  
An example kernel function.
This is not a useful kernel, but it implements the two functions necessary to satisfy the Kernel policy (so that a class can be used whenever an mlpack method calls for a typename Kernel
template parameter.
All that is necessary is a constructor and an Evaluate()
function. More methods could be added; for instance, one useful idea is a constructor which takes parameters for a kernel (for instance, the width of the Gaussian for a Gaussian kernel). However, mlpack methods cannot count on these various constructors existing, which is why most methods allow passing an alreadyinstantiated kernel object (and by default the method will construct the kernel with the default constructor). So, for instance,
will set up kernel PCA using a Gaussian kernel with a width of 5.0, but
will create the kernel with the default constructor. It is important (but not strictly mandatory) that your default constructor still gives a working kernel.
Evaluate()
can (and should) be declared static. However, for greater generalization, mlpack methods expect all kernels to require state and hence must store instantiated kernel functions; this is why a default constructor is necessary. Definition at line 77 of file example_kernel.hpp.

inline 
The default constructor, which takes no parameters.
Because our simple example kernel has no internal parameters that need to be stored, the constructor does not need to do anything. For a more complex example, see the GaussianKernel, which stores an internal parameter.
Definition at line 86 of file example_kernel.hpp.

inlinestatic 
Obtains the convolution integral [integral K(xa)K(bx)dx] for the two vectors.
In this case, because our simple example kernel has no internal parameters, we can declare the function static. For a more complex example which cannot be declared static, see the GaussianKernel, which stores an internal parameter.
VecTypeA  Type of first vector (arma::vec, arma::sp_vec should be expected). 
VecTypeB  Type of second vector (arma::vec, arma::sp_vec). 
a  First vector. 
b  Second vector. 
Definition at line 127 of file example_kernel.hpp.

inlinestatic 
Evaluates the kernel function for two given vectors.
In this case, because our simple example kernel has no internal parameters, we can declare the function static. For a more complex example which cannot be declared static, see the GaussianKernel, which stores an internal parameter.
VecTypeA  Type of first vector (arma::vec, arma::sp_vec should be expected). 
VecTypeB  Type of second vector (arma::vec, arma::sp_vec). 
a  First vector. 
b  Second vector. 
Definition at line 102 of file example_kernel.hpp.

inlinestatic 
Obtains the normalizing volume for the kernel with dimension $dimension$.
In this case, because our simple example kernel has no internal parameters, we can declare the function static. For a more complex example which cannot be declared static, see the GaussianKernel, which stores an internal parameter.
dimension  the dimension of the space. 
Definition at line 140 of file example_kernel.hpp.

inline 
Serializes the kernel.
In this case, the kernel has no members, so we do not need to do anything at all.
Definition at line 110 of file example_kernel.hpp.