: structure holding parameters used by random projection model

Classes
struct	ML::paramsRPROJ
struct	ML::rand_mat< math_t >

Enumerations
enum	ML::random_matrix_type { ML::unset , ML::dense , ML::sparse }

Functions
	ML::rand_mat< math_t >::rand_mat (cudaStream_t stream)
	ML::rand_mat< math_t >::~rand_mat ()
void	ML::rand_mat< math_t >::reset ()
template<typename math_t >
void	ML::RPROJfit (const raft::handle_t &handle, rand_mat< math_t > *random_matrix, paramsRPROJ *params)
template<typename math_t >
void	ML::RPROJtransform (const raft::handle_t &handle, math_t *input, rand_mat< math_t > *random_matrix, math_t *output, paramsRPROJ *params)
size_t	ML::johnson_lindenstrauss_min_dim (size_t n_samples, double eps)

Variables
int	ML::paramsRPROJ::n_samples
int	ML::paramsRPROJ::n_features
int	ML::paramsRPROJ::n_components
double	ML::paramsRPROJ::eps
bool	ML::paramsRPROJ::gaussian_method
double	ML::paramsRPROJ::density
bool	ML::paramsRPROJ::dense_output
int	ML::paramsRPROJ::random_state
rmm::device_uvector< math_t >	ML::rand_mat< math_t >::dense_data
rmm::device_uvector< int >	ML::rand_mat< math_t >::indices
rmm::device_uvector< int >	ML::rand_mat< math_t >::indptr
rmm::device_uvector< math_t >	ML::rand_mat< math_t >::sparse_data
cudaStream_t	ML::rand_mat< math_t >::stream
random_matrix_type	ML::rand_mat< math_t >::type

Detailed Description

Parameters

n_samples	Number of samples
n_features	Number of features (original dimension)
n_components	Number of components (target dimension)
eps	error tolerance used to decide automatically of n_components
gaussian_method	boolean describing random matrix generation method
density	Density of the random matrix
dense_output	boolean describing sparsity of transformed matrix
random_state	seed used by random generator

Enumeration Type Documentation

random_matrix_type

enum ML::random_matrix_type

Enumerator
unset
dense
sparse

Function Documentation

johnson_lindenstrauss_min_dim()

size_t ML::johnson_lindenstrauss_min_dim	(	size_t	n_samples,
		double	eps
	)

rand_mat()

template<typename math_t >

ML::rand_mat< math_t >::rand_mat ( cudaStream_t  stream )

inline

reset()

template<typename math_t >

void ML::rand_mat< math_t >::reset ( )

inline

RPROJfit()

template<typename math_t >

void ML::RPROJfit	(	const raft::handle_t &	handle,
		rand_mat< math_t > *	random_matrix,
		paramsRPROJ *	params
	)

RPROJtransform()

template<typename math_t >

void ML::RPROJtransform	(	const raft::handle_t &	handle,
		math_t *	input,
		rand_mat< math_t > *	random_matrix,
		math_t *	output,
		paramsRPROJ *	params
	)

~rand_mat()

template<typename math_t >

ML::rand_mat< math_t >::~rand_mat ( )

inline

Variable Documentation

dense_data

template<typename math_t >

rmm::device_uvector<math_t> ML::rand_mat< math_t >::dense_data

dense_output

bool ML::paramsRPROJ::dense_output

density

double ML::paramsRPROJ::density

eps

double ML::paramsRPROJ::eps

gaussian_method

bool ML::paramsRPROJ::gaussian_method

indices

template<typename math_t >

rmm::device_uvector<int> ML::rand_mat< math_t >::indices

indptr

template<typename math_t >

rmm::device_uvector<int> ML::rand_mat< math_t >::indptr

n_components

int ML::paramsRPROJ::n_components

n_features

int ML::paramsRPROJ::n_features

n_samples

int ML::paramsRPROJ::n_samples

random_state

int ML::paramsRPROJ::random_state

sparse_data

template<typename math_t >

rmm::device_uvector<math_t> ML::rand_mat< math_t >::sparse_data

stream

template<typename math_t >

cudaStream_t ML::rand_mat< math_t >::stream

type

template<typename math_t >

random_matrix_type ML::rand_mat< math_t >::type