This implements the Line Search algorithm. More...

#include <line_search.h>

Inheritance diagram for quickrank::learning::linear::LineSearch:

Public Member Functions
	LineSearch (unsigned int num_points, double window_size, double reduction_factor, unsigned int max_iterations, unsigned int max_failed_vali, bool adaptive, unsigned int last_only=0)

	LineSearch (const pugi::xml_document &model)

virtual	~LineSearch ()

virtual std::string	name () const
	Returns the name of the ranker. More...

unsigned int	get_last_only () const

void	set_last_only (unsigned int last_only)

void	reset_weights ()

virtual void	learn (std::shared_ptr< data::Dataset > training_dataset, std::shared_ptr< data::Dataset > validation_dataset, std::shared_ptr< metric::ir::Metric > metric, size_t partial_save, const std::string model_filename)
	Executes the learning process. More...

virtual Score	score_document (const Feature *d) const
	Returns the score of a given document. More...

virtual std::shared_ptr< std::vector< double > >	get_weights () const
	Returns the learned weights. More...

virtual bool	update_weights (std::shared_ptr< std::vector< double >> weights)
	Update the weights for the ensemble models (only). More...

virtual pugi::xml_document *	get_xml_model () const
	Return the xml model representing the current object. More...

Public Member Functions inherited from quickrank::learning::LTR_Algorithm
	LTR_Algorithm ()

	LTR_Algorithm (const pugi::xml_document &model)
	Generates a LTR_Algorithm instance from a previously saved XML model. More...

virtual	~LTR_Algorithm ()

	LTR_Algorithm (const LTR_Algorithm &other)=delete
	Avoid inefficient copy constructor. More...

LTR_Algorithm &	operator= (const LTR_Algorithm &)=delete
	Avoid inefficient copy assignment. More...

virtual void	score_dataset (std::shared_ptr< data::Dataset > dataset, Score *scores) const
	Given and input dateset, the current ranker generates scores for each instance and store the in the scores vector. More...

virtual std::shared_ptr< std::vector< Score > >	partial_scores_document (const Feature *d) const
	Returns the partial score of a given document, tree by tree. More...

virtual void	save (std::string model_filename, int suffix=-1) const
	Save the current model to the output_file. More...

virtual void	print_additional_stats (void) const
	Print additional statistics. More...

Static Public Attributes
static const std::string	NAME_ = "LINESEARCH"

Private Member Functions
virtual std::ostream &	put (std::ostream &os) const
	Prints the description of Algorithm, including its parameters. More...

virtual void	preCompute (Feature training_dataset, unsigned int num_samples, unsigned int num_features, Score pre_sum, double weights, Score training_score, unsigned int feature_exclude)

virtual void	score (Feature dataset, unsigned int num_samples, unsigned int num_features, double weights, Score *scores)

Private Attributes
unsigned int	num_points_

double	window_size_

double	reduction_factor_

unsigned int	max_iterations_

unsigned int	max_failed_vali_

bool	adaptive_

unsigned int	train_only_last_

std::vector< double >	best_weights_

Friends
std::ostream &	operator<< (std::ostream &os, const LineSearch &a)
	The output stream operator. More...

Additional Inherited Members
Static Public Member Functions inherited from quickrank::learning::LTR_Algorithm
static std::shared_ptr< LTR_Algorithm >	load_model_from_file (std::string model_filename)
	Load a model from a given XML file. More...

Detailed Description

This implements the Line Search algorithm.

Constructor & Destructor Documentation

quickrank::learning::linear::LineSearch::LineSearch	(	unsigned int	num_points,
		double	window_size,
		double	reduction_factor,
		unsigned int	max_iterations,
		unsigned int	max_failed_vali,
		bool	adaptive,
		unsigned int	last_only = `0`
	)

quickrank::learning::linear::LineSearch::LineSearch ( const pugi::xml_document & model )

quickrank::learning::linear::LineSearch::~LineSearch ( )

virtual

Member Function Documentation

unsigned int quickrank::learning::linear::LineSearch::get_last_only ( ) const

inline

virtual std::shared_ptr<std::vector<double> > quickrank::learning::linear::LineSearch::get_weights ( ) const

inlinevirtual

Returns the learned weights.

Reimplemented from quickrank::learning::LTR_Algorithm.

pugi::xml_document * quickrank::learning::linear::LineSearch::get_xml_model ( ) const

virtual

Return the xml model representing the current object.

Implements quickrank::learning::LTR_Algorithm.

void quickrank::learning::linear::LineSearch::learn	(	std::shared_ptr< data::Dataset >	training_dataset,
		std::shared_ptr< data::Dataset >	validation_dataset,
		std::shared_ptr< metric::ir::Metric >	metric,
		size_t	partial_save,
		const std::string	model_filename
	)

virtual

Executes the learning process.

Parameters

training_dataset	The training dataset.
validation_dataset	The validation training dataset.
metric	The metric to be optimized.
partial_save	Allows to save a partial model every given number of iterations.
model_filename	The file where the model, and the partial models, are saved.

Implements quickrank::learning::LTR_Algorithm.

virtual std::string quickrank::learning::linear::LineSearch::name ( ) const

inlinevirtual

Returns the name of the ranker.

Implements quickrank::learning::LTR_Algorithm.

void quickrank::learning::linear::LineSearch::preCompute	(	Feature *	training_dataset,
		unsigned int	num_samples,
		unsigned int	num_features,
		Score *	pre_sum,
		double *	weights,
		Score *	training_score,
		unsigned int	feature_exclude
	)

privatevirtual

std::ostream & quickrank::learning::linear::LineSearch::put ( std::ostream & os ) const

privatevirtual

Prints the description of Algorithm, including its parameters.

Implements quickrank::learning::LTR_Algorithm.

void quickrank::learning::linear::LineSearch::reset_weights ( )

inline

void quickrank::learning::linear::LineSearch::score	(	Feature *	dataset,
		unsigned int	num_samples,
		unsigned int	num_features,
		double *	weights,
		Score *	scores
	)

privatevirtual

Score quickrank::learning::linear::LineSearch::score_document ( const Feature * d ) const

virtual

Returns the score of a given document.

Implements quickrank::learning::LTR_Algorithm.

void quickrank::learning::linear::LineSearch::set_last_only ( unsigned int last_only )

inline

bool quickrank::learning::linear::LineSearch::update_weights ( std::shared_ptr< std::vector< double >> weights )

virtual

Update the weights for the ensemble models (only).

Default implementation will do nothing (default for non ensemble models).

Reimplemented from quickrank::learning::LTR_Algorithm.

Friends And Related Function Documentation

std::ostream& operator<<	(	std::ostream &	os,
		const LineSearch &	a
	)

friend

The output stream operator.

Member Data Documentation

bool quickrank::learning::linear::LineSearch::adaptive_

private

std::vector<double> quickrank::learning::linear::LineSearch::best_weights_

private

unsigned int quickrank::learning::linear::LineSearch::max_failed_vali_

private

unsigned int quickrank::learning::linear::LineSearch::max_iterations_

private

const std::string quickrank::learning::linear::LineSearch::NAME_ = "LINESEARCH"

static

unsigned int quickrank::learning::linear::LineSearch::num_points_

private

double quickrank::learning::linear::LineSearch::reduction_factor_

private

unsigned int quickrank::learning::linear::LineSearch::train_only_last_

private

double quickrank::learning::linear::LineSearch::window_size_

private

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

include/learning/linear/line_search.h
src/learning/linear/line_search.cc

Public Member Functions

Static Public Attributes

Private Member Functions

Private Attributes

Friends

Additional Inherited Members

Detailed Description

Constructor & Destructor Documentation

Member Function Documentation

Friends And Related Function Documentation

Member Data Documentation