Implementation of the randomized block krylov SVD policy. More...

Public Member Functions
	RandomizedBlockKrylovSVDPolicy (const size_t maxIterations=2, const size_t blockSize=0)
	Use randomized block krylov SVD method to perform the principal components analysis (PCA). More...

void	Apply (const arma::mat &data, const arma::mat &centeredData, arma::mat &transformedData, arma::vec &eigVal, arma::mat &eigvec, const size_t rank)
	Apply Principal Component Analysis to the provided data set using the randomized block krylov SVD method. More...

size_t	MaxIterations () const
	Get the number of iterations for the power method.

size_t &	MaxIterations ()
	Modify the number of iterations for the power method.

size_t	BlockSize () const
	Get the block size.

size_t &	BlockSize ()
	Modify the block size.

Detailed Description

Implementation of the randomized block krylov SVD policy.

Constructor & Destructor Documentation

mlpack::pca::RandomizedBlockKrylovSVDPolicy::RandomizedBlockKrylovSVDPolicy	(	const size_t	maxIterations = `2`,
		const size_t	blockSize = `0`
	)

inline

Use randomized block krylov SVD method to perform the principal components analysis (PCA).

Parameters

maxIterations	Number of iterations for the power method (Default: 2).
blockSize	The block size, must be >= rank (Default: rank + 10).

void mlpack::pca::RandomizedBlockKrylovSVDPolicy::Apply	(	const arma::mat &	data,
		const arma::mat &	centeredData,
		arma::mat &	transformedData,
		arma::vec &	eigVal,
		arma::mat &	eigvec,
		const size_t	rank
	)

inline

Apply Principal Component Analysis to the provided data set using the randomized block krylov SVD method.

Parameters

data	Data matrix.
centeredData	Centered data matrix.
transformedData	Matrix to put results of PCA into.
eigVal	Vector to put eigenvalues into.
eigvec	Matrix to put eigenvectors (loadings) into.
rank	Rank of the decomposition.

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

src/mlpack/methods/pca/decomposition_policies/randomized_block_krylov_method.hpp