sgpp::datadriven::ModelFittingBaseSingleGrid Class Reference

Base class for models operating on a single grid (i.e. More...

#include <ModelFittingBaseSingleGrid.hpp>

Inheritance diagram for sgpp::datadriven::ModelFittingBaseSingleGrid:

Public Member Functions
Grid &	getGrid ()
	Get the underlying grid object for the current model.
DataVector &	getSurpluses ()
	Get the surpluses of the current grid.
	ModelFittingBaseSingleGrid ()
	Default constructor.
	ModelFittingBaseSingleGrid (const ModelFittingBaseSingleGrid &rhs)=delete
	Copy constructor - we cannot deep copy all member variables yet.
	ModelFittingBaseSingleGrid (ModelFittingBaseSingleGrid &&rhs)=default
	Move constructor.
ModelFittingBaseSingleGrid &	operator= (const ModelFittingBaseSingleGrid &rhs)=delete
	Copy assign operator - we cannot deep copy all member variables yet.
ModelFittingBaseSingleGrid &	operator= (ModelFittingBaseSingleGrid &&rhs)=default
	Move assign operator.
std::string	storeFitter ()
virtual	~ModelFittingBaseSingleGrid ()=default
	virtual destructor.
Public Member Functions inherited from sgpp::datadriven::ModelFittingBase
virtual bool	adapt ()=0
	Improve accuracy of the model on the given training data by adaptive refinement of the grid.
virtual double	computeResidual (DataMatrix &validationData) const =0
	Should compute some kind of Residual to evaluate the fit of the model.
virtual double	evaluate (const DataVector &sample)=0
	Evaluate the fitted model at a single data point.
virtual void	evaluate (DataMatrix &samples, DataVector &results)=0
	Evaluate the fitted model on a set of data points.
virtual void	fit (Dataset &dataset)=0
	Fit the grid to the dataset by determining the weights of an initial grid.
virtual void	fit (Dataset &datasetP, Dataset &datasetQ)=0
Dataset *	getDataset ()
FitterConfiguration &	getFitterConfiguration ()
	Get or set the configuration of the fitter object.
const FitterConfiguration &	getFitterConfiguration () const
	Get the configuration of the fitter object.
virtual std::shared_ptr< BlacsProcessGrid >	getProcessGrid () const
	ModelFittingBase ()
	Default constructor.
	ModelFittingBase (const ModelFittingBase &rhs)=delete
	Copy constructor - we cannot deep copy all member variables yet.
	ModelFittingBase (ModelFittingBase &&rhs)=default
	Move constructor.
ModelFittingBase &	operator= (const ModelFittingBase &rhs)=delete
	Copy assign operator - we cannot deep copy all member variables yet.
ModelFittingBase &	operator= (ModelFittingBase &&rhs)=default
	Move assign operator.
virtual void	reset ()=0
	Resets the state of the entire model.
virtual void	resetTraining ()=0
	Resets any trained representations of the model, but does not reset the entire state.
virtual void	update (Dataset &dataset)=0
	Train the grid of an existing model with new samples.
virtual void	update (Dataset &datasetP, Dataset &datasetQ)=0
virtual void	updateRegularization (double lambda)=0
	Updates the regularization parameter lambda of the underlying model.
virtual	~ModelFittingBase ()=default
	virtual destructor.

Protected Attributes
DataVector	alpha
	hierarchical surpluses of the grid.
std::unique_ptr< Grid >	grid
	the sparse grid that approximates the data.
Protected Attributes inherited from sgpp::datadriven::ModelFittingBase
std::unique_ptr< FitterConfiguration >	config
	Configuration object for the fitter.
Dataset *	dataset
	Pointer to sgpp::datadriven::Dataset.
Dataset *	extraDataset
std::unique_ptr< std::set< std::set< size_t > > >	interactions
std::unique_ptr< SLESolver >	solver
	Solver for the learning problem.

Additional Inherited Members
Public Attributes inherited from sgpp::datadriven::ModelFittingBase
bool	verboseSolver
	Whether the Solver produces output or not.
Protected Member Functions inherited from sgpp::datadriven::ModelFittingBase
Grid *	buildGrid (const sgpp::base::GeneralGridConfiguration &gridConfig) const
	Factory member function that generates a grid from configuration.
Grid *	buildGrid (const sgpp::base::GeneralGridConfiguration &gridConfig, const GeometryConfiguration &geometryConfig) const
	Factory member function that generates a grid from configuration.
SLESolver *	buildSolver (const SLESolverConfiguration &config) const
	Factory member function to build the solver for the least squares regression problem according to the config.
std::set< std::set< size_t > >	getInteractions (const GeometryConfiguration &geometryConfig)
void	reconfigureSolver (SLESolver &solver, const SLESolverConfiguration &config) const
	Configure solver based on the desired configuration.

Detailed Description

Base class for models operating on a single grid (i.e.

Least-Squares-Regression and density estimation

Constructor & Destructor Documentation

ModelFittingBaseSingleGrid() [1/3]

sgpp::datadriven::ModelFittingBaseSingleGrid::ModelFittingBaseSingleGrid

(

)

Default constructor.

ModelFittingBaseSingleGrid() [2/3]

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

delete

Copy constructor - we cannot deep copy all member variables yet.

Parameters

rhs	const reference to the scorer object to copy from.

ModelFittingBaseSingleGrid() [3/3]

sgpp::datadriven::ModelFittingBaseSingleGrid::ModelFittingBaseSingleGrid ( ModelFittingBaseSingleGrid &&  rhs )

default

Move constructor.

Parameters

rhs	R-value reference to a scorer object to moved from.

~ModelFittingBaseSingleGrid()

virtual sgpp::datadriven::ModelFittingBaseSingleGrid::~ModelFittingBaseSingleGrid ( )

virtualdefault

virtual destructor.

Member Function Documentation

getGrid()

Grid & sgpp::datadriven::ModelFittingBaseSingleGrid::getGrid ( )

virtual

Get the underlying grid object for the current model.

Returns

the grid object.

Reimplemented from sgpp::datadriven::ModelFittingBase.

References grid.

Referenced by python.uq.analysis.asgc.ASGCKnowledge.ASGCKnowledge::getSparseGridFunction(), python.uq.learner.SimulationLearner.SimulationLearner::learnData(), python.uq.learner.SimulationLearner.SimulationLearner::learnDataWithFolding(), python.uq.learner.SimulationLearner.SimulationLearner::learnDataWithTest(), python.uq.learner.SimulationLearner.SimulationLearner::refineGrid(), storeFitter(), sgpp::datadriven::VisualizerDensityEstimation::storeGrid(), sgpp::datadriven::VisualizerDensityEstimation::storeHeatmapJson(), and sgpp::datadriven::VisualizerDensityEstimation::storeHeatmapJson().

getSurpluses()

DataVector & sgpp::datadriven::ModelFittingBaseSingleGrid::getSurpluses ( )

virtual

Get the surpluses of the current grid.

Returns

vector of surpluses.

Reimplemented from sgpp::datadriven::ModelFittingBase.

References alpha.

Referenced by storeFitter().

operator=() [1/2]

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

delete

Copy assign operator - we cannot deep copy all member variables yet.

Parameters

rhs	const reference to the scorer object to copy from.

Returns

rerefernce to this with updated values.

operator=() [2/2]

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

default

Move assign operator.

Parameters

rhs	R-value reference to an a scorer object to move from.

Returns

rerefernce to this with updated values.

storeFitter()

std::string sgpp::datadriven::ModelFittingBaseSingleGrid::storeFitter

(

)

References getGrid(), getSurpluses(), sgpp::base::Grid::serialize(), and sgpp::base::DataVector::toString().

Member Data Documentation

alpha

DataVector sgpp::datadriven::ModelFittingBaseSingleGrid::alpha

protected

hierarchical surpluses of the grid.

Referenced by sgpp::datadriven::ModelFittingDensityRatioEstimation::adapt(), sgpp::datadriven::ModelFittingLeastSquares::adapt(), sgpp::datadriven::ModelFittingDensityDifferenceEstimationCG::adapt(), sgpp::datadriven::ModelFittingDensityDifferenceEstimationOnOff::adapt(), sgpp::datadriven::ModelFittingDensityEstimationCG::adapt(), sgpp::datadriven::ModelFittingDensityEstimationOnOff::adapt(), sgpp::datadriven::ModelFittingDensityEstimationOnOffParallel::adapt(), sgpp::datadriven::ModelFittingDensityEstimationOnOff::computeResidual(), python.learner.Learner.Learner::doLearningIteration(), sgpp::datadriven::ModelFittingDensityDifferenceEstimationCG::evaluate(), sgpp::datadriven::ModelFittingDensityDifferenceEstimationOnOff::evaluate(), sgpp::datadriven::ModelFittingDensityEstimationCG::evaluate(), sgpp::datadriven::ModelFittingDensityEstimationOnOff::evaluate(), sgpp::datadriven::ModelFittingDensityEstimationOnOffParallel::evaluate(), sgpp::datadriven::ModelFittingDensityRatioEstimation::evaluate(), sgpp::datadriven::ModelFittingLeastSquares::evaluate(), sgpp::datadriven::ModelFittingDensityDifferenceEstimationCG::evaluate(), sgpp::datadriven::ModelFittingDensityDifferenceEstimationOnOff::evaluate(), sgpp::datadriven::ModelFittingDensityEstimationCG::evaluate(), sgpp::datadriven::ModelFittingDensityEstimationOnOff::evaluate(), sgpp::datadriven::ModelFittingDensityEstimationOnOffParallel::evaluate(), sgpp::datadriven::ModelFittingDensityRatioEstimation::evaluate(), sgpp::datadriven::ModelFittingLeastSquares::evaluate(), sgpp::datadriven::ModelFittingDensityEstimationCG::fit(), sgpp::datadriven::ModelFittingDensityEstimationOnOff::fit(), sgpp::datadriven::ModelFittingDensityEstimationOnOffParallel::fit(), sgpp::datadriven::ModelFittingDensityDifferenceEstimationCG::fit(), sgpp::datadriven::ModelFittingDensityDifferenceEstimationOnOff::fit(), sgpp::datadriven::ModelFittingLeastSquares::fit(), sgpp::datadriven::ModelFittingDensityRatioEstimation::fit(), sgpp::datadriven::ModelFittingDensityEstimation::getCoarseningFunctor(), sgpp::datadriven::ModelFittingDensityEstimation::getRefinementFunctor(), getSurpluses(), python.learner.Learner.Learner::learnData(), python.learner.Learner.Learner::learnDataWithTest(), python.uq.learner.Interpolant.Interpolant::learnDataWithTest(), python.uq.dists.SGDEdist.SGDEdist::pdf(), sgpp::datadriven::ModelFittingDensityEstimationOnOff::resetTraining(), sgpp::datadriven::ModelFittingDensityEstimationOnOffParallel::resetTraining(), python.uq.dists.SGDEdist.SGDEdist::toJson(), sgpp::datadriven::ModelFittingDensityEstimationCG::update(), sgpp::datadriven::ModelFittingDensityEstimationOnOff::update(), sgpp::datadriven::ModelFittingDensityEstimationOnOffParallel::update(), sgpp::datadriven::ModelFittingDensityDifferenceEstimationCG::update(), sgpp::datadriven::ModelFittingDensityDifferenceEstimationOnOff::update(), sgpp::datadriven::ModelFittingLeastSquares::update(), and sgpp::datadriven::ModelFittingDensityRatioEstimation::update().

grid

std::unique_ptr<Grid> sgpp::datadriven::ModelFittingBaseSingleGrid::grid

protected

the sparse grid that approximates the data.

Referenced by python.uq.dists.SGDEdist.SGDEdist::__str__(), sgpp::datadriven::ModelFittingDensityEstimation::adapt(), sgpp::datadriven::ModelFittingDensityRatioEstimation::adapt(), sgpp::datadriven::ModelFittingLeastSquares::adapt(), sgpp::datadriven::ModelFittingDensityDifferenceEstimationOnOff::adapt(), sgpp::datadriven::ModelFittingDensityEstimationOnOff::adapt(), sgpp::datadriven::ModelFittingDensityEstimationOnOffParallel::adapt(), python.learner.Learner.Learner::applyData(), python.tools.Matrix::ApplyMatrix(), python.uq.dists.SGDEdist.SGDEdist::cdf(), sgpp::datadriven::ModelFittingDensityEstimationOnOff::computeResidual(), sgpp::datadriven::ModelFittingDensityEstimationOnOffParallel::computeResidual(), python.uq.learner.Interpolant.Interpolant::doLearningIteration(), python.learner.Learner.Learner::doLearningIteration(), python.learner.Classifier.Classifier::evalError(), python.uq.learner.Interpolant.Interpolant::evalError(), sgpp::datadriven::ModelFittingDensityDifferenceEstimationCG::evaluate(), sgpp::datadriven::ModelFittingDensityDifferenceEstimationOnOff::evaluate(), sgpp::datadriven::ModelFittingDensityEstimationCG::evaluate(), sgpp::datadriven::ModelFittingDensityEstimationOnOff::evaluate(), sgpp::datadriven::ModelFittingDensityEstimationOnOffParallel::evaluate(), sgpp::datadriven::ModelFittingDensityRatioEstimation::evaluate(), sgpp::datadriven::ModelFittingLeastSquares::evaluate(), sgpp::datadriven::ModelFittingDensityDifferenceEstimationCG::evaluate(), sgpp::datadriven::ModelFittingDensityDifferenceEstimationOnOff::evaluate(), sgpp::datadriven::ModelFittingDensityEstimationCG::evaluate(), sgpp::datadriven::ModelFittingDensityEstimationOnOff::evaluate(), sgpp::datadriven::ModelFittingDensityEstimationOnOffParallel::evaluate(), sgpp::datadriven::ModelFittingDensityRatioEstimation::evaluate(), sgpp::datadriven::ModelFittingLeastSquares::evaluate(), sgpp::datadriven::ModelFittingDensityEstimationCG::fit(), sgpp::datadriven::ModelFittingDensityEstimationOnOff::fit(), sgpp::datadriven::ModelFittingDensityEstimationOnOffParallel::fit(), sgpp::datadriven::ModelFittingDensityDifferenceEstimationCG::fit(), sgpp::datadriven::ModelFittingDensityDifferenceEstimationOnOff::fit(), sgpp::datadriven::ModelFittingLeastSquares::fit(), sgpp::datadriven::ModelFittingDensityRatioEstimation::fit(), python.tools.Matrix::generateb(), python.controller.CheckpointController.CheckpointController::generateFoldValidationJob(), python.uq.learner.SimulationLearner.SimulationLearner::getCollocationNodes(), getGrid(), python.uq.learner.SimulationLearner.SimulationLearner::getGrid(), python.uq.learner.SimulationLearner.SimulationLearner::getLearner(), sgpp::datadriven::ModelFittingDensityDifferenceEstimationOnOff::isRefinable(), sgpp::datadriven::ModelFittingDensityEstimationOnOff::isRefinable(), sgpp::datadriven::ModelFittingDensityEstimationOnOffParallel::isRefinable(), python.learner.Learner.Learner::learnData(), python.learner.Learner.Learner::learnDataWithFolding(), python.uq.learner.Regressor.Regressor::learnDataWithFolding(), python.learner.Learner.Learner::learnDataWithTest(), python.uq.learner.Regressor.Regressor::learnDataWithTest(), python.controller.CheckpointController.CheckpointController::loadAll(), python.uq.operations.forcePositivity.operationMakePositive.OperationMakePositive::makePositive(), python.uq.operations.forcePositivity.operationMakePositiveFast.OperationMakePositiveFast::makePositive(), python.uq.dists.SGDEdist.SGDEdist::mean(), python.uq.dists.SGDEdist.SGDEdist::pdf(), python.uq.dists.SGDEdist.SGDEdist::ppf(), python.learner.Classifier.Classifier::refineGrid(), python.learner.Regressor.Regressor::refineGrid(), python.uq.learner.Regressor.Regressor::refineGrid(), python.uq.learner.SimulationLearner.SimulationLearner::refineGrid(), sgpp::datadriven::ModelFittingDensityDifferenceEstimationCG::reset(), sgpp::datadriven::ModelFittingDensityDifferenceEstimationOnOff::reset(), sgpp::datadriven::ModelFittingDensityEstimationCG::reset(), sgpp::datadriven::ModelFittingDensityEstimationOnOff::reset(), sgpp::datadriven::ModelFittingDensityEstimationOnOffParallel::reset(), sgpp::datadriven::ModelFittingDensityRatioEstimation::reset(), sgpp::datadriven::ModelFittingLeastSquares::reset(), sgpp::datadriven::ModelFittingDensityEstimationOnOff::resetTraining(), sgpp::datadriven::ModelFittingDensityEstimationOnOffParallel::resetTraining(), python.controller.CheckpointController.CheckpointController::saveGrid(), python.controller.CheckpointController.CheckpointController::setGrid(), python.learner.Learner.Learner::setGrid(), python.uq.learner.Learner.Learner::setGrid(), python.uq.operations.forcePositivity.localFullGridSearch.LocalFullGrid::split(), python.uq.dists.SGDEdist.SGDEdist::toJson(), sgpp::datadriven::ModelFittingDensityEstimationCG::update(), sgpp::datadriven::ModelFittingDensityEstimationOnOff::update(), sgpp::datadriven::ModelFittingDensityEstimationOnOffParallel::update(), sgpp::datadriven::ModelFittingDensityDifferenceEstimationCG::update(), sgpp::datadriven::ModelFittingDensityDifferenceEstimationOnOff::update(), sgpp::datadriven::ModelFittingLeastSquares::update(), sgpp::datadriven::ModelFittingDensityRatioEstimation::update(), sgpp::datadriven::ModelFittingDensityEstimationOnOff::updateRegularization(), sgpp::datadriven::ModelFittingDensityEstimationOnOffParallel::updateRegularization(), and python.uq.dists.SGDEdist.SGDEdist::var().

---

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

• datadriven/src/sgpp/datadriven/datamining/modules/fitting/ModelFittingBaseSingleGrid.hpp
• datadriven/src/sgpp/datadriven/datamining/modules/fitting/ModelFittingBaseSingleGrid.cpp