STK_IClassification.h

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/*--------------------------------------------------------------------*/
/*     Copyright (C) 2004-2016  Serge Iovleff, Université Lille 1, Inria
 
 This program is free software; you can redistribute it and/or modify
 it under the terms of the GNU Lesser 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 Lesser General Public License for more details.
 
 You should have received a copy of the GNU Lesser 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
 
 Contact : S..._Dot_I..._At_stkpp_Dot_org (see copyright for ...)
 */
 
/*
 * Project:  stkpp::Classif
 * created on: 23 juin 2010
 * Purpose:  Interface base class for classification methods.
 * Author:   iovleff, S..._Dot_I..._At_stkpp_Dot_org (see copyright for ...)
 **/
 
#ifndef STK_ICLASSIFICATION_H
#define STK_ICLASSIFICATION_H
 
#include <Sdk.h>
 
namespace STK
{
 
template <class YArray_, class XArray_, class Weights_>
class IClassification: public IRunnerSupervised<YArray_, XArray_, Weights_>
{
  protected:
    typedef IRunnerSupervised<YArray_, XArray_, Weights_> Base;
    using Base::p_x_;
    using Base::p_y_;
    IClassification();
    IClassification( YArray_ const* p_y, XArray_ const* p_x);
    IClassification( YArray_ const& y, XArray_ const& x);
 
  public:
    virtual ~IClassification() {}
 
    inline int nbClass() const { return nbClass_;}
    inline int nbFreeParameter() const { return nbFreeParameter_;}
 
    virtual bool run()
    {
      if (!p_x_ || !p_y_)
      { this->msg_error_ = STKERROR_NO_ARG(IClassification::run,missing data sets);
        return false;
      }
      bool flag=true;
      // perform any initialization step needed before the classification step
      if (!initializeStep()) { flag = false;}
      // compute the classification
      if (!estimationStep()) { flag = false;}
 
      // perform any post-operation needed after the classification step
      if (!finalizeStep()) { flag = false;}
      // Compute the number of parameter of the classification function.
      nbFreeParameter_ = computeNbFreeParameter();
      // create array of the predicted value and compute prediction
      if (!predictionStep()) { flag = false;}
      // return the result of the computations
      this->hasRun_ = true;
      return flag;
    }
    virtual bool run( Weights_ const& weights)
    {
 
      if (!p_x_ || !p_y_)
      { this->msg_error_ = STKERROR_NO_ARG(IClassification::run,missing data sets);
        return false;
      }
      bool flag=true;
      // perform any pre-operation needed before the classification step
      if (!initializeStep()) { flag = false;}
      // compute weighted classification
      if (!estimationStep(weights)) { flag = false;}
 
      // perform any post-operation needed after the classification step
      if (!finalizeStep()) { flag = false;}
      // Compute the number of parameter of the classification function.
      nbFreeParameter_ = computeNbFreeParameter();
      // create array of the predicted value and compute prediction
      if (!predictionStep()) { flag = false;}
 
      // return the result of the computations
      this->hasRun_ = true;
      return flag;
    }
 
  protected:
    int nbClass_;
    int nbFreeParameter_;
 
    virtual bool initializeStep() {return true;}
    virtual bool predictionStep() {return true;};
    virtual bool finalizeStep() {return true;}
 
  private:
    virtual bool estimationStep() =0;
    virtual bool estimationStep(Weights_ const& weights) =0;
    virtual int computeNbFreeParameter() const =0;
};
 
/* Default constructor. Initialize the data members. */
template <class YArray_, class XArray_, class Weights_>
IClassification<YArray_,XArray_,Weights_>::IClassification(): Base(), nbClass_(0), nbFreeParameter_(0) {}
 
/* Constructor. Initialize the data members.
 *  @param p_y,p_x pointer array with the observed output and output
 **/
template <class YArray_, class XArray_, class Weights_>
IClassification<YArray_,XArray_,Weights_>::IClassification( YArray_ const* p_y, XArray_ const* p_x)
                                                          : Base(p_y, p_x)
                                                          , nbClass_(0)
                                                          , nbFreeParameter_(0)
{}
 
/* Constructor. Initialize the data members.
 * @param y,x arrays with the observed output and input
 **/
template <class YArray_, class XArray_, class Weights_>
IClassification<YArray_,XArray_,Weights_>::IClassification( YArray_ const& y, XArray_ const& x)
                                                          : Base(y, x)
                                                          , nbClass_(0)
                                                          , nbFreeParameter_(0)
{}
 
} // namespace STK
 
#endif /* STK_ICLASSIFICATION_H */