sgpp::datadriven::SparseGridMinerSplitting Class Reference

SparseGridMiner models a datamining process that involves a dataset that is first split into validation and training data. More...

#include <SparseGridMinerSplitting.hpp>

Inheritance diagram for sgpp::datadriven::SparseGridMinerSplitting:

Public Member Functions
double	learn (bool verbose) override
	Perform Learning cycle: Get samples from data source and based on the scoring procedure, generalize data by fitting and asses quality of the fit. More...
SparseGridMinerSplitting &	operator= (SparseGridMinerSplitting &&rhs)=default
	Default Move assign operator. More...
SparseGridMinerSplitting &	operator= (const SparseGridMinerSplitting &rhs)=delete
	Default copy assign operator deleted because not all members can be copied. More...
	SparseGridMinerSplitting (DataSourceSplitting *dataSource, ModelFittingBase *fitter, Scorer *scorer)
	Constructor. More...
	SparseGridMinerSplitting (const SparseGridMinerSplitting &rhs)=delete
	Copy constructor deleted - not all members can be copied or cloned . More...
	SparseGridMinerSplitting (SparseGridMinerSplitting &&rhs)=default
	Default Move constructor . More...
	~SparseGridMinerSplitting ()=default
	Default destructor. More...
Public Member Functions inherited from sgpp::datadriven::SparseGridMiner
ModelFittingBase *	getModel ()
	Returns the trained model. More...
SparseGridMiner &	operator= (SparseGridMiner &&rhs)=default
	Default Move assign operator. More...
SparseGridMiner &	operator= (const SparseGridMiner &rhs)=delete
	Default copy assign operator deleted because not all members can be copied. More...
void	setModel (ModelFittingBase *model)
	SparseGridMiner (ModelFittingBase *fitter, Scorer *scorer)
	Constructor. More...
	SparseGridMiner (const SparseGridMiner &rhs)=delete
	Copy constructor deleted - not all members can be copied or cloned . More...
	SparseGridMiner (SparseGridMiner &&rhs)=default
	Default Move constructor . More...
double	test (Dataset &testDataset)
	Evaluate the model on a certain test dataset. More...
virtual	~SparseGridMiner ()=default
	Default destructor. More...

Additional Inherited Members
Protected Attributes inherited from sgpp::datadriven::SparseGridMiner
std::unique_ptr< ModelFittingBase >	fitter
	Fitter that trains a model based on data samples. More...
std::unique_ptr< Scorer >	scorer
	Scorer that quantifies the quality of a fit. More...

Detailed Description

SparseGridMiner models a datamining process that involves a dataset that is first split into validation and training data.

The model is then trained on the training data for several epochs.

Constructor & Destructor Documentation

SparseGridMinerSplitting() [1/3]

sgpp::datadriven::SparseGridMinerSplitting::SparseGridMinerSplitting	(	DataSourceSplitting *	dataSource,
		ModelFittingBase *	fitter,
		Scorer *	scorer
	)

Constructor.

Parameters

dataSource	configured instance of data source object, that will provide samples to learn from. The miner instance will take ownership of the passed object.
fitter	configured instance of fitter object that generalize the model. The miner instance will take ownership of the passed object.
scorer	configured instance of scorer object that will assess the quality of the generalization provided by the fitter on testing data. The miner instance will take ownership of the passed object.

SparseGridMinerSplitting() [2/3]

sgpp::datadriven::SparseGridMinerSplitting::SparseGridMinerSplitting ( const SparseGridMinerSplitting &  rhs )

delete

Copy constructor deleted - not all members can be copied or cloned .

Parameters

rhs	the object to copy from

SparseGridMinerSplitting() [3/3]

sgpp::datadriven::SparseGridMinerSplitting::SparseGridMinerSplitting ( SparseGridMinerSplitting &&  rhs )

default

Default Move constructor .

Parameters

rhs	the object to move from

~SparseGridMinerSplitting()

sgpp::datadriven::SparseGridMinerSplitting::~SparseGridMinerSplitting ( )

default

Default destructor.

Member Function Documentation

learn()

double sgpp::datadriven::SparseGridMinerSplitting::learn ( bool  verbose )

overridevirtual

Perform Learning cycle: Get samples from data source and based on the scoring procedure, generalize data by fitting and asses quality of the fit.

The learning process first divides the data into training and validation data and trains the model for several epochs on the training data.

Implements sgpp::datadriven::SparseGridMiner.

References sgpp::datadriven::RefinementMonitorFactory::createRefinementMonitor(), dataset, sgpp::datadriven::SparseGridMiner::fitter, sgpp::datadriven::Dataset::getNumberInstances(), sgpp::datadriven::RefinementMonitor::pushToBuffer(), sgpp::datadriven::RefinementMonitor::refinementsNecessary(), and sgpp::datadriven::SparseGridMiner::scorer.

operator=() [1/2]

SparseGridMinerSplitting& sgpp::datadriven::SparseGridMinerSplitting::operator= ( SparseGridMinerSplitting &&  rhs )

default

Default Move assign operator.

Parameters

rhs	the object to move from

operator=() [2/2]

SparseGridMinerSplitting& sgpp::datadriven::SparseGridMinerSplitting::operator= ( const SparseGridMinerSplitting &  rhs )

delete

Default copy assign operator deleted because not all members can be copied.

Parameters

rhs	the object to copy from

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

• datadriven/src/sgpp/datadriven/datamining/base/SparseGridMinerSplitting.hpp
• datadriven/src/sgpp/datadriven/datamining/base/SparseGridMinerSplitting.cpp