DAMIS/SOM.h at master · InScience/DAMIS · GitHub

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///////////////////////////////////////////////////////////
//  SOM.h
//  Implementation of the Class SOM
//  Created on:      07-Lie-2013 20:07:32
//  Original author: Povilas
///////////////////////////////////////////////////////////
/*! \file SOM class
    \brief A class of methods and attributes for SOM algorithm.
 */
#if !defined(SOM_H)
#define SOM_H

#include "ObjectMatrix.h"
#include "DimReductionMethod.h"

class SOM : public DimReductionMethod
{

public:
    /*! \fn SOM();
    * \brief A default constructor.
    */
    SOM();
    /*! \fn virtual ~SOM();
    * \brief A destructor.
    */
    virtual ~SOM();
    /*! \fn SOM(int rows, int columns, int eHat);
     * \brief An overloaded constructor that accepts: number of rows, number of columns and hat value.
     * \param int rows - number of som rows
     * \param int columns - number of som columns
     * \param int eHat - learning epoch
     */
    SOM(int rows, int columns, int eHat);

        /*! \fn SOM(int rows, int columns, int eHat);
     * \brief An overloaded constructor that accepts: number of rows, number of columns and hat value.
     * \param int rows - number of som rows
     * \param int columns - number of som columns
     * \param int eHat - learning epoch
     * \param int retWinners - if called SOMMDS then winners aree returned
     */
    SOM(int rows, int columns, int eHat, bool retWinners);
    /*
     * An overloaded constructor that accepts: number of rows, number of columns, hat value and initial matrix.
     */
     /*! \fn SOM(int rows, int columns, int eHat,  ObjectMatrix X);
     * \brief An overloaded constructor that accepts: number of rows, number of columns, hat value and object matrix.
     * \param int rows - number of som rows
     * \param int columns - number of som columns
     * \param int eHat - learning epoch
     * \param ObjectMatrix - initial matrix for SOM
     */
    SOM(int rows, int columns, int eHat, ObjectMatrix X);
    /*! \fn double getQuantizationError();
     *  \brief Returns the quantization error.
     *  \return error - the quantization error.
     */
    double getQuantizationError();
    /*! \fn double getStress();
    *  \brief Returns the quantization error.
    *  \return error - the quantization error.
    */
    double getStress();
    /*! \fn virtual ObjectMatrix getProjection();
     *  \brief Returns the projection matrix \a Y of matrix \a X.
     *  \return Y - the projection matrix.
     */
    virtual ObjectMatrix getProjection();

private:
    /*! \fn double Max(double number1, double number2);
     *  \brief Returns the bigger number.
     *  \param number1 - The first number.
     *  \param number2 - The second number.
     *  \return max
     */
    double Max(double number1, double number2);
    /*! \fn ObjectMatrix Different(ObjectMatrix matrix);
     *  \brief Returns different DataObjects from the ObjectMatrix.
     *  \param matrix - The ObjectMatrix
     *  \return uniqeMatrix - The ObjectMatrix with unique DataObjects.
     */
    ObjectMatrix Different(ObjectMatrix matrix);
    /*!
     * Number of object features i.e. equals to object columns (k_y)
     */
    int k_y;
    /*!
     * Number of learning epoch
     */
    int eHat;
    /*!
     * Neuron winner matrix
     */
    ObjectMatrix nWinner;
    /*!
     * Number or rows is equal to number of ObjectMatrix rows (k_x)
     */
    int k_x;
        /*!
     * If initial matrix with classes or winners mus be returned
     */
    bool returnWinners;

};
#endif // !defined(SOM_H)