regression.hpp

模糊聚類分析源碼。包含教學文件

/*
  
  Context       : Fuzzy Clustering Algorithms

  Author        : Frank Hoeppner, see also AUTHORS file 

  Description   : header of class Regression
                  
  History       : see source file

  Comment       : 
    This file was generated automatically. DO NOT EDIT.

  Copyright     : Copyright (C) 1999-2000 Frank Hoeppner

    This program is free software; you can redistribute it and/or modify
    it under the terms of the GNU General Public License as published by
    the Free Software Foundation; either version 2 of the License, or
    (at your option) any later version.

    This program is distributed in the hope that it will be useful,
    but WITHOUT ANY WARRANTY; without even the implied warranty of
    MERCHANTABILITY or FITNESS FOR A PARTICULAR PURPOSE.  See the
    GNU General Public License for more details.

    You should have received a copy of the GNU General Public License
    along with this program; if not, write to the Free Software
    Foundation, Inc., 59 Temple Place, Suite 330, Boston, MA  02111-1307  USA
*/
/*
  The University of Applied Sciences Oldenburg/Ostfriesland/Wilhelmshaven
  hereby disclaims all copyright interests in the program package `fc' 
  (tool package for fuzzy cluster analysis) written by Frank Hoeppner.
  
  Prof. Haass, President of Vice, 2000-Mar-10
*/

#ifndef Regression_HEADER
#define Regression_HEADER

/* configuration include */
#ifdef HAVE_CONFIG_H
/*
//FILETREE_IFDEF HAVE_CONFIG_H
*/
#include "config.h"
/*
//FILETREE_ENDIF
*/
#endif



// necessary includes
#include "ddl.hpp"
#include "algorithm.hpp"
#include "ReadDDLStream.hpp"
#include "WriteDDLStream.hpp"
#include "ProbMembUpdate.hpp"
#include "AutoMembUpdate.hpp"
#include "DotDistance.hpp"
#include "AltOptLoop.cpp"
#include "ReadDDLStream.hpp"
#include "WriteDDLStream.hpp"
#include "ProbMembUpdate.hpp"
#include "AutoMembUpdate.hpp"
#include "EuclidDistance.hpp"
#include "DotDistance.hpp"
#include "Regression.hpp"
#include "Regression.hpp"
#include "MixedAltOptLoop.hpp"
#include "SelectFeatures.hpp"
//#define INLINE inline

// global types, constants, definitions


// class definition
template < class ANALYSIS >
class Regression
  : public Algorithm<ANALYSIS>
  {
  
  public:
    
    Regression(Algorithm<ANALYSIS>* ap_alg);
    ~Regression();
    virtual void operator()(ANALYSIS&);
    
  protected:
    
    
    Algorithm<ANALYSIS>* mp_succ_alg;
  private:
    
    
    
    
  };

// class related functions and definitions
template <class ALGORITHM> 
inline Regression<typename ALGORITHM::input_type>* 
regr(ALGORITHM* a)
  { return new Regression<typename ALGORITHM::input_type>(a); }
template <class ALGORITHM> 
inline AltOptLoop<typename ALGORITHM::input_type>*
fcrm(ALGORITHM* a)
  {
  NoOperation<typename ALGORITHM::input_type> *p_nop = new NoOperation<typename ALGORITHM::input_type>;; 
  return new AltOptLoop<typename ALGORITHM::input_type>(
    FC_DEPTH_FLAT,
    regr(p_nop),
    dotdist(FC_DOTDIST_ASSIGN,autom(p_nop)),
    ddlwrite(cout,p_nop,false),
    "fcrm",a); 
  }
template <class ALGORITHM> 
inline MixedAltOptLoop<typename ALGORITHM::input_type>*
fm(ALGORITHM* a)
  {
  typedef NoOperation<typename ALGORITHM::input_type> bnop;
  typedef NoOperation< SelectFeatures< typename ALGORITHM::input_type >::select_analysis_type > snop;

  return new MixedAltOptLoop<typename ALGORITHM::input_type>(
    FC_DEPTH_FLAT,
    meancenter(new snop),
    regr(new snop),
    euclid(new snop),
    dotdist(FC_DOTDIST_ADD,new snop),
    autom(new bnop),
    ddlwrite(cout,new bnop,false),
    "fm",a); 
  }

/* inline implementation */




#endif // Regression_HEADER