sgpp::datadriven::SparseGridMiner Class Reference

SparseGridMiner models the entire mining process for data mining with sparse grids. More...

#include <SparseGridMiner.hpp>

Inheritance diagram for sgpp::datadriven::SparseGridMiner:

Public Member Functions
ModelFittingBase *	getModel ()
	Returns the trained model.
Visualizer *	getVisualizer ()
virtual double	learn (bool verbose)=0
	Perform Learning cycle: Get samples from data source and based on the scoring procedure, generalize data by fitting and asses quality of the fit.
SparseGridMiner &	operator= (const SparseGridMiner &rhs)=delete
	Default copy assign operator deleted because not all members can be copied.
SparseGridMiner &	operator= (SparseGridMiner &&rhs)=default
	Default Move assign operator.
void	setModel (ModelFittingBase *model)
	SparseGridMiner (const SparseGridMiner &rhs)=delete
	Copy constructor deleted - not all members can be copied or cloned .
	SparseGridMiner (ModelFittingBase *fitter, Scorer *scorer, Visualizer *visualizer)
	Constructor.
	SparseGridMiner (SparseGridMiner &&rhs)=default
	Default Move constructor .
double	test (Dataset &testDataset)
	Evaluate the model on a certain test dataset.
virtual	~SparseGridMiner ()=default
	Default destructor.

Static Public Member Functions
static void	print (const char *message)
	Print output on one process.
static void	print (const std::string &message)
	Print output on one process.
static void	print (std::ostringstream &messageStream)
	Print output on one process.

Protected Attributes
std::unique_ptr< ModelFittingBase >	fitter
	Fitter that trains a model based on data samples.
std::unique_ptr< Scorer >	scorer
	Scorer that quantifies the quality of a fit.
std::unique_ptr< Visualizer >	visualizer

Detailed Description

SparseGridMiner models the entire mining process for data mining with sparse grids.

It aggregates and automates data input, fitting and validation modules and controls the mining process.

Constructor & Destructor Documentation

SparseGridMiner() [1/3]

sgpp::datadriven::SparseGridMiner::SparseGridMiner	(	ModelFittingBase *	fitter,
		Scorer *	scorer,
		Visualizer *	visualizer
	)

Constructor.

Parameters

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.
visualizer	configured instance of the visualizer object that will execute the visualization module of the model. The miner instance will take ownership of the passed object

SparseGridMiner() [2/3]

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

delete

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

Parameters

rhs	the object to copy from

SparseGridMiner() [3/3]

sgpp::datadriven::SparseGridMiner::SparseGridMiner ( SparseGridMiner &&  rhs )

default

Default Move constructor .

Parameters

rhs	the object to move from

~SparseGridMiner()

virtual sgpp::datadriven::SparseGridMiner::~SparseGridMiner ( )

virtualdefault

Default destructor.

Member Function Documentation

getModel()

ModelFittingBase * sgpp::datadriven::SparseGridMiner::getModel

(

)

Returns the trained model.

Returns

the trained model

getVisualizer()

Visualizer * sgpp::datadriven::SparseGridMiner::getVisualizer

(

)

learn()

virtual double sgpp::datadriven::SparseGridMiner::learn ( bool  verbose )

pure virtual

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

Implemented in sgpp::datadriven::SparseGridMinerCrossValidation, sgpp::datadriven::SparseGridMinerSplitting, and sgpp::datadriven::SparseGridMinerSplittingTwoDatasets.

operator=() [1/2]

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

delete

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

Parameters

rhs	the object to copy from

operator=() [2/2]

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

default

Default Move assign operator.

Parameters

rhs	the object to move from

print() [1/3]

void sgpp::datadriven::SparseGridMiner::print ( const char *  message )

static

Print output on one process.

Parameters

message

References print().

print() [2/3]

void sgpp::datadriven::SparseGridMiner::print ( const std::string &  message )

static

Print output on one process.

Parameters

message

References sgpp::datadriven::BlacsProcessGrid::getCurrentProcess().

Referenced by sgpp::datadriven::SparseGridMinerCrossValidation::learn(), sgpp::datadriven::SparseGridMinerSplitting::learn(), sgpp::datadriven::SparseGridMinerSplitting::optimizeLambda(), print(), and print().

print() [3/3]

void sgpp::datadriven::SparseGridMiner::print ( std::ostringstream &  messageStream )

static

Print output on one process.

Parameters

messageStream

stream with the concatenated message

References print().

setModel()

void sgpp::datadriven::SparseGridMiner::setModel

(

ModelFittingBase *

model

)

References fitter, and sgpp::datadriven::ModelFittingBase::reset().

test()

double sgpp::datadriven::SparseGridMiner::test

(

Dataset &

testDataset

)

Evaluate the model on a certain test dataset.

Parameters

testDataset

dataset used quantify accuracy using sgpp::datadriven::Metric.

Returns

score of the fit.

References fitter, and scorer.

Member Data Documentation

fitter

std::unique_ptr<ModelFittingBase> sgpp::datadriven::SparseGridMiner::fitter

protected

Fitter that trains a model based on data samples.

Referenced by sgpp::datadriven::SparseGridMinerSplitting::evaluateLambda(), sgpp::datadriven::SparseGridMinerCrossValidation::learn(), sgpp::datadriven::SparseGridMinerSplitting::learn(), sgpp::datadriven::SparseGridMinerSplittingTwoDatasets::learn(), sgpp::datadriven::SparseGridMinerSplitting::optimizeLambda(), setModel(), and test().

scorer

std::unique_ptr<Scorer> sgpp::datadriven::SparseGridMiner::scorer

protected

Scorer that quantifies the quality of a fit.

(e.g. cross validation or training with testing)

Referenced by sgpp::datadriven::SparseGridMinerSplitting::evaluateLambda(), sgpp::datadriven::SparseGridMinerCrossValidation::learn(), sgpp::datadriven::SparseGridMinerSplitting::learn(), sgpp::datadriven::SparseGridMinerSplittingTwoDatasets::learn(), and test().

visualizer

std::unique_ptr<Visualizer> sgpp::datadriven::SparseGridMiner::visualizer

protected

Referenced by sgpp::datadriven::SparseGridMinerCrossValidation::learn(), and sgpp::datadriven::SparseGridMinerSplitting::learn().

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

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