mlpack::kernel Namespace Reference

Kernel functions. More...

Classes

class  CauchyKernel
 The Cauchy kernel. More...

 
class  CosineDistance
 The cosine distance (or cosine similarity). More...

 
class  EpanechnikovKernel
 The Epanechnikov kernel, defined as. More...

 
class  ExampleKernel
 An example kernel function. More...

 
class  GaussianKernel
 The standard Gaussian kernel. More...

 
class  HyperbolicTangentKernel
 Hyperbolic tangent kernel. More...

 
class  KernelTraits
 This is a template class that can provide information about various kernels. More...

 
class  KernelTraits< CauchyKernel >
 Kernel traits for the Cauchy kernel. More...

 
class  KernelTraits< CosineDistance >
 Kernel traits for the cosine distance. More...

 
class  KernelTraits< EpanechnikovKernel >
 Kernel traits for the Epanechnikov kernel. More...

 
class  KernelTraits< GaussianKernel >
 Kernel traits for the Gaussian kernel. More...

 
class  KernelTraits< LaplacianKernel >
 Kernel traits of the Laplacian kernel. More...

 
class  KernelTraits< SphericalKernel >
 Kernel traits for the spherical kernel. More...

 
class  KernelTraits< TriangularKernel >
 Kernel traits for the triangular kernel. More...

 
class  KMeansSelection
 Implementation of the kmeans sampling scheme. More...

 
class  LaplacianKernel
 The standard Laplacian kernel. More...

 
class  LinearKernel
 The simple linear kernel (dot product). More...

 
class  NystroemMethod
 
class  OrderedSelection
 
class  PolynomialKernel
 The simple polynomial kernel. More...

 
class  PSpectrumStringKernel
 The p-spectrum string kernel. More...

 
class  RandomSelection
 
class  SphericalKernel
 The spherical kernel, which is 1 when the distance between the two argument points is less than or equal to the bandwidth, or 0 otherwise. More...

 
class  TriangularKernel
 The trivially simple triangular kernel, defined by. More...

 

Detailed Description

Kernel functions.

This namespace contains kernel functions, which evaluate some kernel function $ K(x, y) $ for some arbitrary vectors $ x $ and $ y $ of the same dimension. The single restriction on the function $ K(x, y) $ is that it must satisfy Mercer's condition:

\[ \int \int K(x, y) g(x) g(y) dx dy \ge 0 \]

for all square integrable functions $ g(x) $.

The kernels in this namespace all implement the KernelType policy. For more information, see The KernelType policy documentation.