mlpack::kernel::KernelTraits< EpanechnikovKernel > Class Template Reference

Kernel traits for the Epanechnikov kernel. More...

Static Public Attributes
static const bool	IsNormalized = true
	The Epanechnikov kernel is normalized: K(x, x) = 1 for all x. More...
static const bool	UsesSquaredDistance = true
	The Epanechnikov kernel includes a squared distance. More...

Detailed Description

template<>
class mlpack::kernel::KernelTraits< EpanechnikovKernel >

Kernel traits for the Epanechnikov kernel.

Definition at line 108 of file epanechnikov_kernel.hpp.

Member Data Documentation

const bool mlpack::kernel::KernelTraits< EpanechnikovKernel >::IsNormalized = true

static

The Epanechnikov kernel is normalized: K(x, x) = 1 for all x.

Definition at line 112 of file epanechnikov_kernel.hpp.

const bool mlpack::kernel::KernelTraits< EpanechnikovKernel >::UsesSquaredDistance = true

static

The Epanechnikov kernel includes a squared distance.

Definition at line 114 of file epanechnikov_kernel.hpp.

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The documentation for this class was generated from the following file:

• src/mlpack/core/kernels/epanechnikov_kernel.hpp