ML::paramsPCATemplate< enum_solver > Class Template Reference

structure for pca parameters. Ref: http://scikit-learn.org/stable/modules/generated/sklearn.decomposition.PCA.html More...

#include <params.hpp>

Inheritance diagram for ML::paramsPCATemplate< enum_solver >:

Collaboration diagram for ML::paramsPCATemplate< enum_solver >:

Public Attributes
bool	copy = true
bool	whiten = false
Public Attributes inherited from ML::paramsTSVDTemplate< solver >
std::size_t	n_components
solver	algorithm
Public Attributes inherited from ML::paramsSolver
float	tol = 0.0
std::uint32_t	n_iterations = 15
int	verbose = 0
Public Attributes inherited from ML::params
std::size_t	n_rows
std::size_t	n_cols
int	gpu_id = 0

Detailed Description

template<typename enum_solver = solver>
class ML::paramsPCATemplate< enum_solver >

structure for pca parameters. Ref: http://scikit-learn.org/stable/modules/generated/sklearn.decomposition.PCA.html

Parameters

n_components	Number of components to keep. if n_components is not set all components are kept:
copy	If False, data passed to fit are overwritten and running fit(X).transform(X) will not yield the expected results, use fit_transform(X) instead.
whiten	When True (False by default) the components_ vectors are multiplied by the square root of n_samples and then divided by the singular values to ensure uncorrelated outputs with unit component-wise variances.
algorithm	the solver to be used in PCA.
tol	Tolerance for singular values computed by svd_solver == ‘arpack’ or svd_solver == ‘COV_EIG_JACOBI’
n_iterations	Number of iterations for the power method computed by jacobi method (svd_solver == 'COV_EIG_JACOBI').
verbose	0: no error message printing, 1: print error messages

Member Data Documentation

copy

template<typename enum_solver = solver>

bool ML::paramsPCATemplate< enum_solver >::copy = true

whiten

template<typename enum_solver = solver>

bool ML::paramsPCATemplate< enum_solver >::whiten = false

---

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

• include/cuml/decomposition/params.hpp