CV_alpha_k< cv_strat, err_eval, k_imp, valid_err_ret > Class Template Reference

Template class for performing cross-validation on the regularization parameter and the number of PPCs: derived-from-CV_base thorugh CRTP ('CV_alpha_k' its template D parameter). More...

#include <CV_alpha_k.hpp>

Inheritance diagram for CV_alpha_k< cv_strat, err_eval, k_imp, valid_err_ret >:

Public Member Functions
template<typename STOR_OBJ, typename STRATEGY>
	CV_alpha_k (STOR_OBJ &&Data, STRATEGY &&strategy, const std::vector< double > &alphas, const std::vector< int > &k_s, double toll, const pred_func_t< K_IMP::YES > &pred_f, int number_threads)
	Constructor for derived class: constructs firstly CV_base<CV_alpha_k,...>
double	alpha_best () const
	Getter for the best regularization parameter.
double	k_best () const
	Getter for the best number of retained PPCs.
std::vector< double >	valid_errors_best_pairs () const
	Getter for validation errors for the best pairs.
std::vector< std::vector< double > >	valid_errors () const
	Getter for validation errors.
double	best_valid_error () const
	Getter for the best validation error.
void	best_param_search ()
	Retaining the best pair regularization parameter-number of retained PPCs.
Public Member Functions inherited from CV_base< CV_alpha_k< cv_strat, err_eval, k_imp, valid_err_ret >, cv_strat, err_eval, k_imp, valid_err_ret >
double	err_valid_set_eval (const KO_Traits::StoringVector &pred, const KO_Traits::StoringVector &valid, int number_threads) const
	Evaluation of the loss between prediction on validation set and validation set: estimate of L2 norm loss. Tag-dispacther.
	CV_base (STOR_OBJ &&Data, STRATEGY &&strategy, int number_threads)
	Constructor for the class.
KO_Traits::StoringMatrix	Data () const
	Getter for the data matrix.
cv_strategy< cv_strat >	strategy () const
	Getter for the training/validation set splitting.
int	number_threads () const
	Getter for the number of threads for OMP.

Detailed Description

template<CV_STRAT cv_strat, CV_ERR_EVAL err_eval, K_IMP k_imp, VALID_ERR_RET valid_err_ret>
class CV_alpha_k< cv_strat, err_eval, k_imp, valid_err_ret >

Template class for performing cross-validation on the regularization parameter and the number of PPCs: derived-from-CV_base thorugh CRTP ('CV_alpha_k' its template D parameter).

Template Parameters

cv_strat	strategy for splitting training/validation sets
err_eval	how to evaluate the loss between prediction on validation set and validation set
k_imp	if k is imposed or has to be found through explanatory power criterion (necessary k_imp=K_IMP::YES since k is imposed at each cv iteration)
valid_err_ret	if validation error are stored

Derived class. Polymorphism is known at compile time thanks to Curiously Recursive Template Pattern (CRTP)

Constructor & Destructor Documentation

CV_alpha_k()

template<CV_STRAT cv_strat, CV_ERR_EVAL err_eval, K_IMP k_imp, VALID_ERR_RET valid_err_ret>

template<typename STOR_OBJ, typename STRATEGY>

CV_alpha_k< cv_strat, err_eval, k_imp, valid_err_ret >::CV_alpha_k ( STOR_OBJ && Data, STRATEGY && strategy, const std::vector< double > & alphas, const std::vector< int > & k_s, double toll, const pred_func_t< K_IMP::YES > & pred_f, int number_threads )

inline

Constructor for derived class: constructs firstly CV_base<CV_alpha_k,...>

Parameters

Data	fts data matrix
strategy	splitting training/validation strategy
alphas	input space for the regularization parameter
k_s	input space for number of retained PPCs
toll	tolerance between consecutive validation errors for looking for element with bigger value in the input space
pred_f	function to make validation set prediction (overloading with k imposed)
number_threads	number of threads for OMP

Universal constructor: move semantic used to optimazing handling big size objects

Member Function Documentation

alpha_best()

template<CV_STRAT cv_strat, CV_ERR_EVAL err_eval, K_IMP k_imp, VALID_ERR_RET valid_err_ret>

double CV_alpha_k< cv_strat, err_eval, k_imp, valid_err_ret >::alpha_best ( ) const

inline

Getter for the best regularization parameter.

Returns

the private m_alpha_best

best_param_search()

template<CV_STRAT cv_strat, CV_ERR_EVAL err_eval, K_IMP k_imp, VALID_ERR_RET valid_err_ret>

void CV_alpha_k< cv_strat, err_eval, k_imp, valid_err_ret >::best_param_search ( )

inline

Retaining the best pair regularization parameter-number of retained PPCs.

for each element of the input space for regularization parameters, a cross-validation on the number of retained PPCs is performed. Consequently, the best pair is looked for within this ones.

Note

eventual usage of 'pragma' directive for OMP

best_valid_error()

template<CV_STRAT cv_strat, CV_ERR_EVAL err_eval, K_IMP k_imp, VALID_ERR_RET valid_err_ret>

double CV_alpha_k< cv_strat, err_eval, k_imp, valid_err_ret >::best_valid_error ( ) const

inline

Getter for the best validation error.

Returns

the private m_best_valid_error

k_best()

template<CV_STRAT cv_strat, CV_ERR_EVAL err_eval, K_IMP k_imp, VALID_ERR_RET valid_err_ret>

double CV_alpha_k< cv_strat, err_eval, k_imp, valid_err_ret >::k_best ( ) const

inline

Getter for the best number of retained PPCs.

Returns

the private m_k_best

valid_errors()

template<CV_STRAT cv_strat, CV_ERR_EVAL err_eval, K_IMP k_imp, VALID_ERR_RET valid_err_ret>

std::vector< std::vector< double > > CV_alpha_k< cv_strat, err_eval, k_imp, valid_err_ret >::valid_errors ( ) const

inline

Getter for validation errors.

Returns

the private m_valid_errors

valid_errors_best_pairs()

template<CV_STRAT cv_strat, CV_ERR_EVAL err_eval, K_IMP k_imp, VALID_ERR_RET valid_err_ret>

std::vector< double > CV_alpha_k< cv_strat, err_eval, k_imp, valid_err_ret >::valid_errors_best_pairs ( ) const

inline

Getter for validation errors for the best pairs.

Returns

the private m_valid_errors_best_pairs

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

• src/CV_alpha_k.hpp