mlpack::kernel::NystroemMethod< KernelType, PointSelectionPolicy > Class Template Reference

Public Member Functions
	NystroemMethod (const arma::mat &data, KernelType &kernel, const size_t rank)
	Create the NystroemMethod object. More...
void	Apply (arma::mat &output)
	Apply the low-rank factorization to obtain an output matrix G such that K' = G * G^T. More...
void	GetKernelMatrix (const arma::mat *data, arma::mat &miniKernel, arma::mat &semiKernel)
	Construct the kernel matrix with matrix that contains the selected points. More...
void	GetKernelMatrix (const arma::Col< size_t > &selectedPoints, arma::mat &miniKernel, arma::mat &semiKernel)
	Construct the kernel matrix with the selected points. More...

Private Attributes
const arma::mat &	data
	The reference dataset. More...
KernelType &	kernel
	The locally stored kernel, if it is necessary. More...
const size_t	rank
	Rank used for matrix approximation. More...

Detailed Description

template<typename KernelType, typename PointSelectionPolicy = KMeansSelection<>>
class mlpack::kernel::NystroemMethod< KernelType, PointSelectionPolicy >

Definition at line 28 of file nystroem_method.hpp.

Constructor & Destructor Documentation

template<typename KernelType, typename PointSelectionPolicy = KMeansSelection<>>

mlpack::kernel::NystroemMethod< KernelType, PointSelectionPolicy >::NystroemMethod	(	const arma::mat &	data,
		KernelType &	kernel,
		const size_t	rank
	)

Create the NystroemMethod object.

The constructor here does not really do anything.

Parameters

data	Data matrix.
kernel	Kernel to be used for computation.
rank	Rank to be used for matrix approximation.

Member Function Documentation

template<typename KernelType, typename PointSelectionPolicy = KMeansSelection<>>

void mlpack::kernel::NystroemMethod< KernelType, PointSelectionPolicy >::Apply

(

arma::mat &

output

)

Apply the low-rank factorization to obtain an output matrix G such that K' = G * G^T.

Parameters

output

Matrix to store kernel approximation into.

Referenced by mlpack::kpca::NystroemKernelRule< KernelType, PointSelectionPolicy >::ApplyKernelMatrix().

template<typename KernelType, typename PointSelectionPolicy = KMeansSelection<>>

void mlpack::kernel::NystroemMethod< KernelType, PointSelectionPolicy >::GetKernelMatrix	(	const arma::mat *	data,
		arma::mat &	miniKernel,
		arma::mat &	semiKernel
	)

Construct the kernel matrix with matrix that contains the selected points.

Parameters

data	Data matrix pointer.
miniKernel	to store the constructed mini-kernel matrix in.
miniKernel	to store the constructed semi-kernel matrix in.

template<typename KernelType, typename PointSelectionPolicy = KMeansSelection<>>

void mlpack::kernel::NystroemMethod< KernelType, PointSelectionPolicy >::GetKernelMatrix	(	const arma::Col< size_t > &	selectedPoints,
		arma::mat &	miniKernel,
		arma::mat &	semiKernel
	)

Construct the kernel matrix with the selected points.

Parameters

points	Indices of selected points.
miniKernel	to store the constructed mini-kernel matrix in.
miniKernel	to store the constructed semi-kernel matrix in.

Member Data Documentation

template<typename KernelType, typename PointSelectionPolicy = KMeansSelection<>>

const arma::mat& mlpack::kernel::NystroemMethod< KernelType, PointSelectionPolicy >::data

private

The reference dataset.

Definition at line 73 of file nystroem_method.hpp.

template<typename KernelType, typename PointSelectionPolicy = KMeansSelection<>>

KernelType& mlpack::kernel::NystroemMethod< KernelType, PointSelectionPolicy >::kernel

private

The locally stored kernel, if it is necessary.

Definition at line 75 of file nystroem_method.hpp.

template<typename KernelType, typename PointSelectionPolicy = KMeansSelection<>>

const size_t mlpack::kernel::NystroemMethod< KernelType, PointSelectionPolicy >::rank

private

Rank used for matrix approximation.

Definition at line 77 of file nystroem_method.hpp.

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

• src/mlpack/methods/nystroem_method/nystroem_method.hpp