SG++-Doxygen-Documentation
sgpp::datadriven::DatasetGenerator Class Referenceabstract

#include <DatasetGenerator.hpp>

Inheritance diagram for sgpp::datadriven::DatasetGenerator:
sgpp::datadriven::Friedman1Generator sgpp::datadriven::Friedman2Generator sgpp::datadriven::Friedman3Generator

Public Member Functions

virtual void createData (size_t offset, size_t size, base::DataMatrix &trainingData, base::DataVector &classes)=0
 
virtual size_t getDims ()=0
 
virtual double normal (double mean, double stddev)
 generate normally distributed random variable see http://de.wikipedia.org/wiki/Box-Muller-Methode uses rand(), make sure to call srand yourself More...
 
virtual double uniform (double a, double b)
 
virtual ~DatasetGenerator ()
 

Constructor & Destructor Documentation

◆ ~DatasetGenerator()

sgpp::datadriven::DatasetGenerator::~DatasetGenerator ( )
virtual

Member Function Documentation

◆ createData()

virtual void sgpp::datadriven::DatasetGenerator::createData ( size_t  offset,
size_t  size,
base::DataMatrix trainingData,
base::DataVector classes 
)
pure virtual

◆ getDims()

virtual size_t sgpp::datadriven::DatasetGenerator::getDims ( )
pure virtual

◆ normal()

double sgpp::datadriven::DatasetGenerator::normal ( double  mean,
double  stddev 
)
virtual

generate normally distributed random variable see http://de.wikipedia.org/wiki/Box-Muller-Methode uses rand(), make sure to call srand yourself

Parameters
meanmean of distribution
stddevstd deviation of distribution
Returns
normally distributed random var

References M_PI.

Referenced by sgpp::datadriven::Friedman1Generator::createData(), sgpp::datadriven::Friedman2Generator::createData(), and sgpp::datadriven::Friedman3Generator::createData().

◆ uniform()

double sgpp::datadriven::DatasetGenerator::uniform ( double  a,
double  b 
)
virtual

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