SG++-Doxygen-Documentation
sgpp::datadriven::Learner Class Reference

This class implements standard sparse grid regression with an arbitrary regularization operator. More...

#include <Learner.hpp>

Inheritance diagram for sgpp::datadriven::Learner:
sgpp::datadriven::LearnerBase

Public Member Functions

 Learner (sgpp::datadriven::RegularizationType &regularization, const bool isRegression, const bool isVerbose=true)
 Constructor. More...
 
virtual ~Learner ()
 Destructor. More...
 
- Public Member Functions inherited from sgpp::datadriven::LearnerBase
void dumpFunction (std::string tFilename, size_t resolution)
 simple dump of sparse grid function into file, e.g. More...
 
void dumpGrid (std::string tFilename)
 simple dump of grid points into file, e.g. More...
 
virtual double getAccuracy (sgpp::base::DataMatrix &testDataset, const sgpp::base::DataVector &classesReference, const double threshold=0.0)
 compute the accuracy for given testDataset. More...
 
virtual double getAccuracy (const sgpp::base::DataVector &classesComputed, const sgpp::base::DataVector &classesReference, const double threshold=0.0)
 compute the accuracy for given testDataset. More...
 
sgpp::base::DataVectorgetAlpha ()
 
virtual ClassificatorQuality getCassificatorQuality (sgpp::base::DataMatrix &testDataset, const sgpp::base::DataVector &classesReference, const double threshold=0.0)
 compute the quality for given testDataset, classification ONLY! test is automatically called in order to determine the regression values of the current learner More...
 
virtual ClassificatorQuality getCassificatorQuality (const sgpp::base::DataVector &classesComputed, const sgpp::base::DataVector &classesReference, const double threshold=0.0)
 compute the quality for given testDataset, classification ONLY! More...
 
sgpp::base::GridgetGrid ()
 
bool getIsRegression () const
 determines the current mode More...
 
bool getIsVerbose () const
 determines the current verbose mode of learner More...
 
std::vector< std::pair< size_t, double > > getRefinementExecTimes ()
 
 LearnerBase (const bool isRegression, const bool isVerbose=true)
 Constructor. More...
 
 LearnerBase (const LearnerBase &copyMe)
 Copy-Constructor. More...
 
virtual void multTranspose (sgpp::base::DataMatrix &dataset, sgpp::base::DataVector &multiplier, sgpp::base::DataVector &result)
 
virtual void predict (sgpp::base::DataMatrix &testDataset, sgpp::base::DataVector &classesComputed)
 executes a Regression test for a given dataset and returns the result More...
 
void setIsVerbose (const bool isVerbose)
 sets the current verbose mode of learner More...
 
void setReuseCoefficients (bool reuseCoefficients)
 
void setSolverVerbose (bool solverVerbose)
 
void store (std::string tGridFilename, std::string tAlphaFilename)
 store the grid and its current coefficients into files for further usage. More...
 
virtual LearnerTiming train (sgpp::base::DataMatrix &trainDataset, sgpp::base::DataVector &classes, const sgpp::base::RegularGridConfiguration &GridConfig, const sgpp::solver::SLESolverConfiguration &SolverConfigRefine, const sgpp::solver::SLESolverConfiguration &SolverConfigFinal, const sgpp::base::AdaptivityConfiguration &AdaptConfig, bool testAccDuringAdapt, const double lambdaRegularization, sgpp::base::DataMatrix *testDataset=nullptr, sgpp::base::DataVector *testClasses=nullptr)
 Learning a dataset with spatially adaptive sparse grids. More...
 
LearnerTiming train (sgpp::base::DataMatrix &trainDataset, sgpp::base::DataVector &classes, const sgpp::base::RegularGridConfiguration &GridConfig, const sgpp::solver::SLESolverConfiguration &SolverConfig, const double lambdaRegularization)
 Learning a dataset with regular sparse grids. More...
 
virtual ~LearnerBase ()
 Destructor. More...
 

Protected Member Functions

virtual std::unique_ptr< sgpp::datadriven::DMSystemMatrixBasecreateDMSystem (sgpp::base::DataMatrix &trainDataset, double lambda)
 construct system matrix More...
 
- Protected Member Functions inherited from sgpp::datadriven::LearnerBase
virtual void InitializeGrid (const sgpp::base::RegularGridConfiguration &GridConfig)
 Initialize the grid and its coefficients. More...
 
virtual void postProcessing (const sgpp::base::DataMatrix &trainDataset, const sgpp::solver::SLESolverType &solver, const size_t numNeededIterations)
 Hook-Method for post-processing after each refinement learning. More...
 
virtual void preProcessing ()
 Hook-Method for pre-processing before starting learning. More...
 

Protected Attributes

sgpp::datadriven::RegularizationType CMode
 regularization mode More...
 
- Protected Attributes inherited from sgpp::datadriven::LearnerBase
std::unique_ptr< sgpp::base::DataVectoralpha
 the grid's coefficients More...
 
size_t currentRefinementStep
 the current refinment step during training More...
 
double execTime
 execution time More...
 
std::vector< std::pair< size_t, double > > ExecTimeOnStep
 
double GByte
 number of transferred Gbytes More...
 
double GFlop
 number of executed Floating Point operations More...
 
std::unique_ptr< sgpp::base::Gridgrid
 sparse grid object More...
 
bool isRegression
 is regression selected More...
 
bool isTrained
 is the grid trained More...
 
bool isVerbose
 is verbose output enabled More...
 
bool reuseCoefficients
 shall the coefficients be reused between refinement steps More...
 
bool solverVerbose
 sets the verbose option for the solver More...
 
double stepExecTime
 execution time for current refinement to calculate the GFlops at the current timestep only otherwise accumulated GFlops (all refinement steps) are calculated More...
 
double stepGByte
 number of transferred Gbytes in the current refinement step More...
 
double stepGFlop
 number of executed Floating Point operations in the current refinement step More...
 

Detailed Description

This class implements standard sparse grid regression with an arbitrary regularization operator.

Constructor & Destructor Documentation

sgpp::datadriven::Learner::Learner ( sgpp::datadriven::RegularizationType regularization,
const bool  isRegression,
const bool  isVerbose = true 
)

Constructor.

Parameters
regularizationenum that gives the regurlarization method
isRegressionflag for regression
isVerboseflag for verbose output
sgpp::datadriven::Learner::~Learner ( )
virtual

Destructor.

Member Function Documentation

Member Data Documentation

sgpp::datadriven::RegularizationType sgpp::datadriven::Learner::CMode
protected

regularization mode

Referenced by createDMSystem().


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