SG++-Doxygen-Documentation
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Fitter object that encapsulates the usage of sparse grid based regression with identity as regularization. More...
#include <ModelFittingLeastSquares.hpp>
Public Member Functions | |
double | evaluate (const DataVector &sample) override |
Evaluate the fitted regression model at a single data point - requires a trained grid. More... | |
void | evaluate (DataMatrix &samples, DataVector &results) override |
Evaluate the fitted model on a set of data points - requires a trained grid. More... | |
void | fit (Dataset &dataset) override |
Fit the grid to the given dataset by determining the weights of the initial grid by a least squares approach. More... | |
ModelFittingLeastSquares (const FitterConfigurationLeastSquares &config) | |
Constructor. More... | |
bool | refine () override |
Improve accuracy of the fit on the given training data by adaptive refinement of the grid and recalculate weights. More... | |
void | reset () override |
Resets the state of the entire model. More... | |
void | update (Dataset &dataset) override |
Train the grid of an existing model with new samples. 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 | |
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 | ~ModelFittingBase ()=default |
virtual destructor. 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... | |
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... | |
Fitter object that encapsulates the usage of sparse grid based regression with identity as regularization.
Allows usage of different grids, different solvers and different regularization techniques based on the provided configuration objects.
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explicit |
Constructor.
config | configuration object that specifies grid, refinement, and regularization |
References sgpp::datadriven::ModelFittingBase::buildSolver(), sgpp::datadriven::ModelFittingBase::config, and sgpp::datadriven::ModelFittingBase::solver.
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overridevirtual |
Evaluate the fitted regression model at a single data point - requires a trained grid.
sample | vector with the coordinates in all dimensions of that sample. |
Implements sgpp::datadriven::ModelFittingBase.
References sgpp::datadriven::ModelFittingBaseSingleGrid::alpha, sgpp::op_factory::createOperationEval(), sgpp::base::OperationEval::eval(), and sgpp::datadriven::ModelFittingBaseSingleGrid::grid.
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overridevirtual |
Evaluate the fitted model on a set of data points - requires a trained grid.
samples | matrix where each row represents a sample and the columns contain the coordinates in all dimensions of that sample. |
results | vector where each row will contain the evaluation of the respective sample on the current model. |
Implements sgpp::datadriven::ModelFittingBase.
References sgpp::datadriven::ModelFittingBaseSingleGrid::alpha, sgpp::datadriven::ModelFittingBase::config, sgpp::op_factory::createOperationMultipleEval(), sgpp::base::OperationMultipleEval::eval(), and sgpp::datadriven::ModelFittingBaseSingleGrid::grid.
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overridevirtual |
Fit the grid to the given dataset by determining the weights of the initial grid by a least squares approach.
dataset | the training dataset that is used to fit the model. |
Implements sgpp::datadriven::ModelFittingBase.
References sgpp::datadriven::ModelFittingBaseSingleGrid::alpha, sgpp::datadriven::ModelFittingBase::buildGrid(), sgpp::datadriven::ModelFittingBase::config, sgpp::datadriven::ModelFittingBase::dataset, sgpp::datadriven::Dataset::getDimension(), sgpp::datadriven::ModelFittingBaseSingleGrid::grid, and reset().
Referenced by update().
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overridevirtual |
Improve accuracy of the fit on the given training data by adaptive refinement of the grid and recalculate weights.
Implements sgpp::datadriven::ModelFittingBase.
References sgpp::datadriven::ModelFittingBaseSingleGrid::alpha, sgpp::datadriven::ModelFittingBase::config, sgpp::datadriven::ModelFittingBaseSingleGrid::grid, and sgpp::base::DataVector::resizeZero().
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overridevirtual |
Resets the state of the entire model.
Implements sgpp::datadriven::ModelFittingBase.
References sgpp::datadriven::ModelFittingBaseSingleGrid::alpha, chess::b, sgpp::datadriven::ModelFittingBase::config, sgpp::datadriven::ModelFittingBase::dataset, DEFAULT_RES_THRESHOLD, sgpp::datadriven::Dataset::getData(), sgpp::base::Grid::getSize(), sgpp::datadriven::Dataset::getTargets(), sgpp::datadriven::ModelFittingBase::reconfigureSolver(), sgpp::datadriven::ModelFittingBase::solver, and sgpp::datadriven::ModelFittingBase::verboseSolver.
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overridevirtual |
Train the grid of an existing model with new samples.
dataset | the training dataset that is used to fit the model. |
Implements sgpp::datadriven::ModelFittingBase.
References sgpp::datadriven::ModelFittingBaseSingleGrid::alpha, sgpp::datadriven::ModelFittingBase::config, sgpp::datadriven::ModelFittingBase::dataset, fit(), sgpp::datadriven::ModelFittingBaseSingleGrid::grid, lambda, and reset().