SG++-Doxygen-Documentation
Public Member Functions | Protected Attributes | List of all members
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:
sgpp::datadriven::ModelFittingBase sgpp::datadriven::ModelFittingDensityEstimation sgpp::datadriven::ModelFittingLeastSquares sgpp::datadriven::ModelFittingDensityEstimationCG sgpp::datadriven::ModelFittingDensityEstimationOnOff

Public Member Functions

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 bool refine ()=0
 Improve accuracy of the model on the given training data by adaptive refinement of the grid. 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 Attributes

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...
 
- 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...
 

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.

References alpha.

◆ ModelFittingBaseSingleGrid() [2/3]

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

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

Parameters
rhsconst reference to the scorer object to copy from.

◆ ModelFittingBaseSingleGrid() [3/3]

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

Move constructor.

Parameters
rhsR-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 ( )

Get the underlying grid object for the current model.

Returns
the grid object.

References grid.

◆ getSurpluses()

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

Get the surpluses of the current grid.

Returns
vector of surpluses.

References alpha.

◆ operator=() [1/2]

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

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

Parameters
rhsconst 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
rhsR-value reference to an a scorer object to move from.
Returns
rerefernce to this with updated values.

Member Data Documentation

◆ alpha

DataVector sgpp::datadriven::ModelFittingBaseSingleGrid::alpha
protected

hierarchical surpluses of the grid.

Referenced by sgpp::datadriven::ModelFittingLeastSquares::evaluate(), sgpp::datadriven::ModelFittingDensityEstimationOnOff::evaluate(), sgpp::datadriven::ModelFittingDensityEstimationCG::evaluate(), sgpp::datadriven::ModelFittingLeastSquares::fit(), sgpp::datadriven::ModelFittingDensityEstimationOnOff::fit(), sgpp::datadriven::ModelFittingDensityEstimationCG::fit(), sgpp::datadriven::ModelFittingDensityEstimation::getRefinementFunctor(), getSurpluses(), ModelFittingBaseSingleGrid(), sgpp::datadriven::ModelFittingLeastSquares::refine(), sgpp::datadriven::ModelFittingDensityEstimationCG::refine(), sgpp::datadriven::ModelFittingDensityEstimationOnOff::refine(), python.learner.Classifier.Classifier::refineGrid(), sgpp::datadriven::ModelFittingLeastSquares::reset(), sgpp::datadriven::ModelFittingLeastSquares::update(), sgpp::datadriven::ModelFittingDensityEstimationOnOff::update(), and sgpp::datadriven::ModelFittingDensityEstimationCG::update().

◆ grid

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

the sparse grid that approximates the data.

Referenced by python.uq.learner.Interpolant.Interpolant::doLearningIteration(), python.learner.Classifier.Classifier::evalError(), python.uq.learner.Interpolant.Interpolant::evalError(), sgpp::datadriven::ModelFittingLeastSquares::evaluate(), sgpp::datadriven::ModelFittingDensityEstimationCG::evaluate(), sgpp::datadriven::ModelFittingDensityEstimationOnOff::evaluate(), sgpp::datadriven::ModelFittingLeastSquares::fit(), sgpp::datadriven::ModelFittingDensityEstimationCG::fit(), sgpp::datadriven::ModelFittingDensityEstimationOnOff::fit(), python.uq.learner.SimulationLearner.SimulationLearner::getCollocationNodes(), python.uq.learner.SimulationLearner.SimulationLearner::getGrid(), getGrid(), python.uq.learner.SimulationLearner.SimulationLearner::getLearner(), sgpp::datadriven::ModelFittingDensityEstimationOnOff::isRefinable(), python.uq.learner.Regressor.Regressor::learnData(), python.uq.learner.Regressor.Regressor::learnDataWithFolding(), python.uq.learner.Regressor.Regressor::learnDataWithTest(), sgpp::datadriven::ModelFittingLeastSquares::refine(), sgpp::datadriven::ModelFittingDensityEstimation::refine(), sgpp::datadriven::ModelFittingDensityEstimationOnOff::refine(), python.learner.Classifier.Classifier::refineGrid(), python.learner.Regressor.Regressor::refineGrid(), python.uq.learner.Regressor.Regressor::refineGrid(), python.uq.learner.SimulationLearner.SimulationLearner::refineGrid(), sgpp::datadriven::ModelFittingDensityEstimationOnOff::reset(), sgpp::datadriven::ModelFittingLeastSquares::update(), sgpp::datadriven::ModelFittingDensityEstimationCG::update(), sgpp::datadriven::ModelFittingDensityEstimationOnOff::update(), python.learner.Classifier.Classifier::updateResults(), python.learner.Regressor.Regressor::updateResults(), and python.uq.learner.Regressor.Regressor::updateResults().

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