Abstract super class to encapsulate density estimation models such as using offline/-online splitting or conjugate gradients in order to solve the system. More...

#include <ModelFittingDensityEstimation.hpp>

Inheritance diagram for sgpp::datadriven::ModelFittingDensityEstimation:

Public Member Functions
virtual void	fit (DataMatrix &dataset)=0
	Fit the grid to the given dataset by determining the surpluses of the initial grid by the SGDE approach. More...

sgpp::base::RefinementFunctor *	getRefinementFunctor ()
	Returns the refinement functor suitable for the model settings. More...

	ModelFittingDensityEstimation ()
	Default constructor. More...

virtual bool	refine (size_t newNoPoints, std::list< size_t > *deletedGridPoints)=0
	Performs a refinement given the new grid size and the points to coarsened. More...

bool	refine () override
	Improve accuracy of the fit on the given training data by adaptive refinement of the grid and recalculate weights. More...

virtual void	update (DataMatrix &samples)=0
	Updates the model based on new data samples (streaming, batch learning). More...

Public Member Functions inherited from sgpp::datadriven::ModelFittingBaseSingleGrid
Grid &	getGrid ()
	Get the underlying grid object for the current model. More...

DataVector &	getSurpluses ()
	Get the surpluses of the current grid. More...

	ModelFittingBaseSingleGrid ()
	Default constructor. More...

	ModelFittingBaseSingleGrid (const ModelFittingBaseSingleGrid &rhs)=delete
	Copy constructor - we cannot deep copy all member variables yet. More...

	ModelFittingBaseSingleGrid (ModelFittingBaseSingleGrid &&rhs)=default
	Move constructor. More...

ModelFittingBaseSingleGrid &	operator= (const ModelFittingBaseSingleGrid &rhs)=delete
	Copy assign operator - we cannot deep copy all member variables yet. More...

ModelFittingBaseSingleGrid &	operator= (ModelFittingBaseSingleGrid &&rhs)=default
	Move assign operator. More...

virtual	~ModelFittingBaseSingleGrid ()=default
	virtual destructor. More...

Public Member Functions inherited from sgpp::datadriven::ModelFittingBase
virtual double	evaluate (const DataVector &sample)=0
	Evaluate the fitted model at a single data point. More...

virtual void	evaluate (DataMatrix &samples, DataVector &results)=0
	Evaluate the fitted model on a set of data points. More...

virtual void	fit (Dataset &dataset)=0
	Polymorphic clone pattern. More...

const FitterConfiguration &	getFitterConfiguration () const
	Get the configuration of the fitter object. More...

	ModelFittingBase ()
	Default constructor. More...

	ModelFittingBase (const ModelFittingBase &rhs)=delete
	Copy constructor - we cannot deep copy all member variables yet. More...

	ModelFittingBase (ModelFittingBase &&rhs)=default
	Move constructor. More...

ModelFittingBase &	operator= (const ModelFittingBase &rhs)=delete
	Copy assign operator - we cannot deep copy all member variables yet. More...

ModelFittingBase &	operator= (ModelFittingBase &&rhs)=default
	Move assign operator. More...

virtual void	reset ()=0
	Resets the state of the entire model. More...

virtual void	update (Dataset &dataset)=0
	Train the grid of an existing model with new samples. More...

virtual	~ModelFittingBase ()=default
	virtual destructor. More...

Protected Member Functions
virtual bool	isRefinable ()=0
	Function that indicates whether a model is refinable at all (certain on/off settings do not allow for refinement) More...

Protected Member Functions inherited from sgpp::datadriven::ModelFittingBase
Grid *	buildGrid (const RegularGridConfiguration &gridConfig) const
	Factory member function that generates a grid from configuration. More...

SLESolver *	buildSolver (const SLESolverConfiguration &config) const
	Factory member function to build the solver for the least squares regression problem according to the config. More...

void	reconfigureSolver (SLESolver &solver, const SLESolverConfiguration &config) const
	Configure solver based on the desired configuration. More...

Protected Attributes
size_t	refinementsPerformed
	Count the amount of refinement operations performed on the current dataset. More...

Protected Attributes inherited from sgpp::datadriven::ModelFittingBaseSingleGrid
DataVector	alpha
	hierarchical surpluses of the grid. More...

std::unique_ptr< Grid >	grid
	the sparse grid that approximates the data. More...

Protected Attributes inherited from sgpp::datadriven::ModelFittingBase
std::unique_ptr< FitterConfiguration >	config
	Configuration object for the fitter. More...

Dataset *	dataset
	Pointer to sgpp::datadriven::Dataset. More...

std::unique_ptr< SLESolver >	solver
	Solver for the learning problem. More...

Additional Inherited Members
Public Attributes inherited from sgpp::datadriven::ModelFittingBase
bool	verboseSolver
	Whether the Solver produces output or not. More...

Detailed Description

Abstract super class to encapsulate density estimation models such as using offline/-online splitting or conjugate gradients in order to solve the system.

Constructor & Destructor Documentation

◆ ModelFittingDensityEstimation()

sgpp::datadriven::ModelFittingDensityEstimation::ModelFittingDensityEstimation ( )

Default constructor.

Member Function Documentation

◆ fit()

virtual void sgpp::datadriven::ModelFittingDensityEstimation::fit ( DataMatrix & dataset )

pure virtual

Fit the grid to the given dataset by determining the surpluses of the initial grid by the SGDE approach.

Requires only data samples and no targets (since those are irrelevant for the density estimation whatsoever)

Parameters

dataset the training dataset that is used to fit the model.

Implemented in sgpp::datadriven::ModelFittingDensityEstimationCG, and sgpp::datadriven::ModelFittingDensityEstimationOnOff.

◆ getRefinementFunctor()

RefinementFunctor * sgpp::datadriven::ModelFittingDensityEstimation::getRefinementFunctor ( )

Returns the refinement functor suitable for the model settings.

Returns: pointer to a refinement functor that suits the model settings

References sgpp::datadriven::ModelFittingBaseSingleGrid::alpha, sgpp::datadriven::ModelFittingBase::config, and sgpp::base::AdaptivityConfiguration::refinementFunctorType.

Referenced by refine().

◆ isRefinable()

virtual bool sgpp::datadriven::ModelFittingDensityEstimation::isRefinable ( )

protectedpure virtual

Function that indicates whether a model is refinable at all (certain on/off settings do not allow for refinement)

Returns: whether the model is refinable

Implemented in sgpp::datadriven::ModelFittingDensityEstimationOnOff.

Referenced by refine().

◆ refine() [1/2]

virtual bool sgpp::datadriven::ModelFittingDensityEstimation::refine	(	size_t	newNoPoints,
		std::list< size_t > *	deletedGridPoints
	)

pure virtual

Performs a refinement given the new grid size and the points to coarsened.

Parameters

newNoPoints	the grid size after refinement and coarsening
deletedGridPoints	a list of indexes for grid points that will be removed

Returns: if the grid was refined (true)

Implemented in sgpp::datadriven::ModelFittingDensityEstimationCG, and sgpp::datadriven::ModelFittingDensityEstimationOnOff.

◆ refine() [2/2]

bool sgpp::datadriven::ModelFittingDensityEstimation::refine ( )

overridevirtual

Improve accuracy of the fit on the given training data by adaptive refinement of the grid and recalculate weights.

Returns: true if refinement could be performed based on the refinement configuration, else false.

Implements sgpp::datadriven::ModelFittingBase.

References getRefinementFunctor(), sgpp::datadriven::ModelFittingBaseSingleGrid::grid, isRefinable(), and refinementsPerformed.

◆ update()

virtual void sgpp::datadriven::ModelFittingDensityEstimation::update ( DataMatrix & samples )

pure virtual

Updates the model based on new data samples (streaming, batch learning).

Requires only the data samples and no targets (since those are irrelevant for the density estimation whatsoever)

Parameters

samples the new data samples

Implemented in sgpp::datadriven::ModelFittingDensityEstimationCG, and sgpp::datadriven::ModelFittingDensityEstimationOnOff.

Member Data Documentation

◆ refinementsPerformed

size_t sgpp::datadriven::ModelFittingDensityEstimation::refinementsPerformed

protected

Count the amount of refinement operations performed on the current dataset.

Referenced by refine(), sgpp::datadriven::ModelFittingDensityEstimationCG::reset(), and sgpp::datadriven::ModelFittingDensityEstimationOnOff::reset().

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

datadriven/src/sgpp/datadriven/datamining/modules/fitting/ModelFittingDensityEstimation.hpp
datadriven/src/sgpp/datadriven/datamining/modules/fitting/ModelFittingDensityEstimation.cpp

Public Member Functions

Protected Member Functions

Protected Attributes

Additional Inherited Members

Detailed Description

Constructor & Destructor Documentation

◆ ModelFittingDensityEstimation()

Member Function Documentation

◆ fit()

◆ getRefinementFunctor()

◆ isRefinable()

◆ refine() [1/2]

◆ refine() [2/2]

◆ update()

Member Data Documentation

◆ refinementsPerformed