slope::NoScreening Class Reference

No screening rule - uses all variables. More...

#include <screening.h>

Inheritance diagram for slope::NoScreening:

Collaboration diagram for slope::NoScreening:

Public Member Functions
std::vector< int >	initialize (const std::vector< int > &full_set, int alpha_max_ind) override
	Initialize the screening rule at the start of the path algorithm.
std::vector< int >	screen (Eigen::VectorXd &gradient, const Eigen::ArrayXd &lambda_curr, const Eigen::ArrayXd &lambda_prev, const Eigen::VectorXd &beta, const std::vector< int > &full_set) override
	Screen for the next path step.
bool	checkKktViolations (Eigen::VectorXd &gradient, const Eigen::VectorXd &beta, const Eigen::ArrayXd &lambda_curr, std::vector< int > &working_set, const Eigen::MatrixXd &x, const Eigen::MatrixXd &residual, const Eigen::VectorXd &x_centers, const Eigen::VectorXd &x_scales, JitNormalization jit_normalization, const std::vector< int > &full_set) override
	Check for KKT violations and update working set if necessary.
bool	checkKktViolations (Eigen::VectorXd &gradient, const Eigen::VectorXd &beta, const Eigen::ArrayXd &lambda_curr, std::vector< int > &working_set, const Eigen::SparseMatrix< double > &x, const Eigen::MatrixXd &residual, const Eigen::VectorXd &x_centers, const Eigen::VectorXd &x_scales, JitNormalization jit_normalization, const std::vector< int > &full_set) override
	Check for KKT violations with sparse matrix input.
std::string	toString () const override
	Get string representation of the screening rule.
Public Member Functions inherited from slope::ScreeningRule
virtual	~ScreeningRule ()=default
	Virtual destructor.

Additional Inherited Members
Protected Attributes inherited from slope::ScreeningRule
std::vector< int >	strong_set
	Strong set of variables.

Detailed Description

No screening rule - uses all variables.

Definition at line 149 of file screening.h.

Member Function Documentation

checkKktViolations() [1/2]

bool slope::NoScreening::checkKktViolations ( Eigen::VectorXd &  gradient, const Eigen::VectorXd &  beta, const Eigen::ArrayXd &  lambda_curr, std::vector< int > &  working_set, const Eigen::MatrixXd &  x, const Eigen::MatrixXd &  residual, const Eigen::VectorXd &  x_centers, const Eigen::VectorXd &  x_scales, JitNormalization  jit_normalization, const std::vector< int > &  full_set  )

overridevirtual

Check for KKT violations and update working set if necessary.

Parameters

gradient	The gradient vector
beta	Current beta coefficients
lambda_curr	Current lambda values
working_set	Current working set (will be updated if violations found)
x	Design matrix
residual	Current residuals
x_centers	Centers for normalization
x_scales	Scales for normalization
jit_normalization	Whether to use JIT normalization
full_set	Full set of features

Returns

True if no violations found, false otherwise

Implements slope::ScreeningRule.

Definition at line 94 of file screening.cpp.

checkKktViolations() [2/2]

bool slope::NoScreening::checkKktViolations ( Eigen::VectorXd &  gradient, const Eigen::VectorXd &  beta, const Eigen::ArrayXd &  lambda_curr, std::vector< int > &  working_set, const Eigen::SparseMatrix< double > &  x, const Eigen::MatrixXd &  residual, const Eigen::VectorXd &  x_centers, const Eigen::VectorXd &  x_scales, JitNormalization  jit_normalization, const std::vector< int > &  full_set  )

overridevirtual

Check for KKT violations with sparse matrix input.

Parameters

gradient	The gradient vector
beta	Current beta coefficients
lambda_curr	Current lambda values
working_set	Current working set (will be updated if violations found)
x	Design matrix (sparse format)
residual	Current residuals
x_centers	Centers for normalization
x_scales	Scales for normalization
jit_normalization	Whether to use JIT normalization
full_set	Full set of features

Returns

True if no violations found, false otherwise

Implements slope::ScreeningRule.

Definition at line 109 of file screening.cpp.

initialize()

std::vector< int > slope::NoScreening::initialize ( const std::vector< int > &  full_set, int  alpha_max_ind  )

overridevirtual

Initialize the screening rule at the start of the path algorithm.

Parameters

full_set	The full set of feature indices
alpha_max_ind	The index of the feature with maximum absolute gradient

Returns

The initial working set

Implements slope::ScreeningRule.

Definition at line 77 of file screening.cpp.

screen()

std::vector< int > slope::NoScreening::screen ( Eigen::VectorXd &  gradient, const Eigen::ArrayXd &  lambda_curr, const Eigen::ArrayXd &  lambda_prev, const Eigen::VectorXd &  beta, const std::vector< int > &  full_set  )

overridevirtual

Screen for the next path step.

Parameters

gradient	The gradient vector
lambda_curr	Current lambda values
lambda_prev	Previous lambda values
beta	Current beta coefficients
full_set	Full set of features

Returns

Working set for the current path step

Implements slope::ScreeningRule.

Definition at line 83 of file screening.cpp.

toString()

std::string slope::NoScreening::toString ( ) const

overridevirtual

Get string representation of the screening rule.

Returns

Name of the screening rule

Implements slope::ScreeningRule.

Definition at line 124 of file screening.cpp.

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

• src/slope/screening.h
• src/slope/screening.cpp