ArtificialDistributions.h

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#ifndef _ArtificialDistributions_H_
#define _ArtificialDistributions_H_


#include <ReClaM/Dataset.h>
#include <Array/Array2D.h>


class Chessboard : public DataSource
{
public:
    Chessboard(int dim = 2, int size = 4);

    ~Chessboard();


    bool GetData(Array<double>& data, Array<double>& target, int count);

protected:
    int size;
};


class NoisyChessboard : public Chessboard
{
public:
    NoisyChessboard(int dim = 2, int size = 4, double noiselevel = 0.4);

    ~NoisyChessboard();


    bool GetData(Array<double>& data, Array<double>& target, int count);

protected:
    double noiselevel;
};


class NoisyInterval : public DataSource
{
public:
    NoisyInterval(double bayesRate, int dimensions = 1);

    ~NoisyInterval();


    bool GetData(Array<double>& data, Array<double>& target, int count);

protected:
    double bayesRate;
    int dimensions;
};


class SphereDistribution1 : public DataSource
{
public:
    SphereDistribution1(int dim);

    ~SphereDistribution1();


    bool GetData(Array<double>& data, Array<double>& target, int count);

protected:
    int dimension;
};


class SparseDistribution : public DataSource
{
public:
    SparseDistribution(int n, int m, int k);

    ~SparseDistribution();


    bool GetData(Array<double>& data, Array<double>& target, int count);

protected:
    int dim1;
    int dim2;
    int num;
};


class TransformedProblem : public DataSource
{
public:
    TransformedProblem(DataSource& source, Array2D<double>& transformation);

    ~TransformedProblem();


    bool GetData(Array<double>& data, Array<double>& target, int count);

protected:
    DataSource& base;
    Array2D<double> transformation;
};


class MultiClassTestProblem : public DataSource
{
public:
    MultiClassTestProblem(double epsilon = 0.5);
    ~MultiClassTestProblem();

    bool GetData(Array<double>& data, Array<double>& target, int count);

protected:
    double m_epsilon;
};


#endif