quickrank::optimization::post_learning::pruning::Cleaver Class Reference

This implements various strategies for pruning ensembles. More...

#include <cleaver.h>

Inheritance diagram for quickrank::optimization::post_learning::pruning::Cleaver:

Public Types
enum	PruningMethod {   PruningMethod::RANDOM, PruningMethod::LOW_WEIGHTS, PruningMethod::SKIP, PruningMethod::LAST,   PruningMethod::QUALITY_LOSS, PruningMethod::SCORE_LOSS }
Public Types inherited from quickrank::optimization::Optimization
enum	OptimizationAlgorithm { OptimizationAlgorithm::EPRUNING }

Public Member Functions
	Cleaver (double pruning_rate)
	Cleaver (double pruning_rate, std::shared_ptr< learning::linear::LineSearch > lineSearch)
	Cleaver (const pugi::xml_document &model)
std::string	name () const
	Returns the name of the optimizer. More...
virtual PruningMethod	pruning_method () const =0
	Returns the pruning method of the algorithm. More...
virtual bool	line_search_pre_pruning () const =0
virtual bool	need_partial_score_dataset () const
virtual void	pruning (std::set< unsigned int > &pruned_estimators, std::shared_ptr< data::Dataset > dataset, std::shared_ptr< metric::ir::Metric > scorer)=0
void	optimize (std::shared_ptr< quickrank::learning::LTR_Algorithm > algo, std::shared_ptr< quickrank::data::Dataset > training_dataset, std::shared_ptr< quickrank::data::Dataset > validation_dataset, std::shared_ptr< quickrank::metric::ir::Metric > metric, size_t partial_save, const std::string model_filename)
virtual std::shared_ptr< data::Dataset >	filter_dataset (std::shared_ptr< data::Dataset > dataset, std::set< unsigned int > &pruned_estimators) const
	Process the dataset filtering out features with 0-weight. More...
virtual pugi::xml_document *	get_xml_model () const
	Return the xml model representing the current object. More...
virtual std::vector< float > &	get_weigths ()
	Returns the learned weights. More...
Public Member Functions inherited from quickrank::optimization::post_learning::PostLearningOptimization
bool	is_pre_learning () const
Public Member Functions inherited from quickrank::optimization::Optimization
	Optimization ()
	Optimization (const pugi::xml_document &model)
	Generates a LTR_Algorithm instance from a previously saved XML model. More...
virtual	~Optimization ()=default
	Optimization (const Optimization &other)=delete
	Avoid inefficient copy constructor. More...
Optimization &	operator= (const Optimization &)=delete
	Avoid inefficient copy assignment. More...
virtual void	optimize (std::shared_ptr< learning::LTR_Algorithm > algo, 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)=0
	Executes the optimization process. More...
virtual void	save (std::string model_filename, int suffix=-1) const
	Save the current model to the output_file. More...

Static Public Member Functions
static PruningMethod	getPruningMethod (std::string name)
static std::string	getPruningMethod (PruningMethod pruningMethod)
Static Public Member Functions inherited from quickrank::optimization::Optimization
static std::shared_ptr< Optimization >	load_model_from_file (std::string model_filename)
	Load a model from a given XML file. More...
static OptimizationAlgorithm	getOptimizationAlgorithm (std::string name)
static std::string	getPruningMethod (OptimizationAlgorithm optAlgo)

Static Public Attributes
static const std::vector< std::string >	pruningMethodNames
static const std::string	NAME_ = "CLEAVER"
Static Public Attributes inherited from quickrank::optimization::Optimization
static const std::vector< std::string >	optimizationAlgorithmNames

Protected Member Functions
std::ostream &	put (std::ostream &os) const
	Prints the description of Algorithm, including its parameters. More...
virtual void	score (data::Dataset *dataset, Score *scores) const
virtual void	import_weights_from_line_search (std::set< unsigned int > &pruned_estimators)

Protected Attributes
double	pruning_rate_
unsigned int	estimators_to_prune_
unsigned int	estimators_to_select_
std::shared_ptr< learning::linear::LineSearch >	lineSearch_
std::vector< float >	weights_

Detailed Description

This implements various strategies for pruning ensembles.

This optimization algorithm expect the datasets to be in the partial scores format (i.e., a column for each ensemble, with the partial score returned by that ensamble on each document (row of the original dataset)

Member Enumeration Documentation

enum quickrank::optimization::post_learning::pruning::Cleaver::PruningMethod

strong

Enumerator
RANDOM
LOW_WEIGHTS
SKIP
LAST
QUALITY_LOSS
SCORE_LOSS

Constructor & Destructor Documentation

quickrank::optimization::post_learning::pruning::Cleaver::Cleaver

(

double

pruning_rate

)

quickrank::optimization::post_learning::pruning::Cleaver::Cleaver	(	double	pruning_rate,
		std::shared_ptr< learning::linear::LineSearch >	lineSearch
	)

quickrank::optimization::post_learning::pruning::Cleaver::Cleaver

(

const pugi::xml_document &

model

)

Member Function Documentation

std::shared_ptr< data::Dataset > quickrank::optimization::post_learning::pruning::Cleaver::filter_dataset ( std::shared_ptr< data::Dataset >  dataset, std::set< unsigned int > &  pruned_estimators  ) const

virtual

Process the dataset filtering out features with 0-weight.

virtual std::vector<float>& quickrank::optimization::post_learning::pruning::Cleaver::get_weigths ( )

inlinevirtual

Returns the learned weights.

pugi::xml_document * quickrank::optimization::post_learning::pruning::Cleaver::get_xml_model ( ) const

virtual

Return the xml model representing the current object.

Implements quickrank::optimization::Optimization.

static PruningMethod quickrank::optimization::post_learning::pruning::Cleaver::getPruningMethod ( std::string  name )

inlinestatic

static std::string quickrank::optimization::post_learning::pruning::Cleaver::getPruningMethod ( PruningMethod  pruningMethod )

inlinestatic

void quickrank::optimization::post_learning::pruning::Cleaver::import_weights_from_line_search ( std::set< unsigned int > &  pruned_estimators )

protectedvirtual

virtual bool quickrank::optimization::post_learning::pruning::Cleaver::line_search_pre_pruning ( ) const

pure virtual

Implemented in quickrank::optimization::post_learning::pruning::LowWeightsPruning, quickrank::optimization::post_learning::pruning::QualityLossPruning, quickrank::optimization::post_learning::pruning::RandomPruning, quickrank::optimization::post_learning::pruning::ScoreLossPruning, quickrank::optimization::post_learning::pruning::LastPruning, and quickrank::optimization::post_learning::pruning::SkipPruning.

std::string quickrank::optimization::post_learning::pruning::Cleaver::name ( ) const

inlinevirtual

Returns the name of the optimizer.

Implements quickrank::optimization::Optimization.

virtual bool quickrank::optimization::post_learning::pruning::Cleaver::need_partial_score_dataset ( ) const

inlinevirtual

Implements quickrank::optimization::Optimization.

void quickrank::optimization::post_learning::pruning::Cleaver::optimize	(	std::shared_ptr< quickrank::learning::LTR_Algorithm >	algo,
		std::shared_ptr< quickrank::data::Dataset >	training_dataset,
		std::shared_ptr< quickrank::data::Dataset >	validation_dataset,
		std::shared_ptr< quickrank::metric::ir::Metric >	metric,
		size_t	partial_save,
		const std::string	model_filename
	)

virtual void quickrank::optimization::post_learning::pruning::Cleaver::pruning ( std::set< unsigned int > &  pruned_estimators, std::shared_ptr< data::Dataset >  dataset, std::shared_ptr< metric::ir::Metric >  scorer  )

pure virtual

Implemented in quickrank::optimization::post_learning::pruning::LowWeightsPruning, quickrank::optimization::post_learning::pruning::QualityLossPruning, quickrank::optimization::post_learning::pruning::RandomPruning, quickrank::optimization::post_learning::pruning::ScoreLossPruning, quickrank::optimization::post_learning::pruning::LastPruning, and quickrank::optimization::post_learning::pruning::SkipPruning.

virtual PruningMethod quickrank::optimization::post_learning::pruning::Cleaver::pruning_method ( ) const

pure virtual

Returns the pruning method of the algorithm.

Implemented in quickrank::optimization::post_learning::pruning::LowWeightsPruning, quickrank::optimization::post_learning::pruning::QualityLossPruning, quickrank::optimization::post_learning::pruning::RandomPruning, quickrank::optimization::post_learning::pruning::ScoreLossPruning, quickrank::optimization::post_learning::pruning::LastPruning, and quickrank::optimization::post_learning::pruning::SkipPruning.

std::ostream & quickrank::optimization::post_learning::pruning::Cleaver::put ( std::ostream &  os ) const

protectedvirtual

Prints the description of Algorithm, including its parameters.

Implements quickrank::optimization::Optimization.

void quickrank::optimization::post_learning::pruning::Cleaver::score ( data::Dataset *  dataset, Score *  scores  ) const

protectedvirtual

Member Data Documentation

unsigned int quickrank::optimization::post_learning::pruning::Cleaver::estimators_to_prune_

protected

unsigned int quickrank::optimization::post_learning::pruning::Cleaver::estimators_to_select_

protected

std::shared_ptr<learning::linear::LineSearch> quickrank::optimization::post_learning::pruning::Cleaver::lineSearch_

protected

const std::string quickrank::optimization::post_learning::pruning::Cleaver::NAME_ = "CLEAVER"

static

double quickrank::optimization::post_learning::pruning::Cleaver::pruning_rate_

protected

const std::vector< std::string > quickrank::optimization::post_learning::pruning::Cleaver::pruningMethodNames

static

Initial value:

= {
    "RANDOM", "LOW_WEIGHTS", "SKIP", "LAST", "QUALITY_LOSS", "SCORE_LOSS"
}

std::vector<float> quickrank::optimization::post_learning::pruning::Cleaver::weights_

protected

---

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

• include/optimization/post_learning/pruning/cleaver.h
• src/optimization/post_learning/pruning/cleaver.cc