MKLMulticlass.h

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/*
 * 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 3 of the License, or
 * (at your option) any later version.
 *
 * Written (W) 2009 Alexander Binder
 * Copyright (C) 2009 Fraunhofer Institute FIRST and Max-Planck-Society
 *
 * Update to patch 0.10.0 - thanks to Eric aka Yoo (thereisnoknife@gmail.com)
 *
 */

#ifndef MKLMulticlass_H_
#define MKLMulticlass_H_

#include <shogun/lib/config.h>
#include <shogun/base/SGObject.h>
#include <shogun/kernel/Kernel.h>
#include <shogun/kernel/CombinedKernel.h>
#include <shogun/multiclass/GMNPSVM.h>
#include <shogun/classifier/mkl/MKLMulticlassGLPK.h>
#include <shogun/classifier/mkl/MKLMulticlassGradient.h>
#include <shogun/multiclass/MulticlassSVM.h>


namespace shogun
{

class CMKLMulticlass : public CMulticlassSVM
{
public:
   CMKLMulticlass();

   CMKLMulticlass(float64_t C, CKernel* k, CLabels* lab);

   virtual ~CMKLMulticlass();

   virtual inline EMachineType get_classifier_type()
   { return CT_MKLMULTICLASS; }

   float64_t* getsubkernelweights(int32_t & numweights);

   void set_mkl_epsilon(float64_t eps );

   void set_max_num_mkliters(int32_t maxnum);

   virtual void set_mkl_norm(float64_t norm);

protected:
   CMKLMulticlass( const CMKLMulticlass & cm);

   CMKLMulticlass operator=( const CMKLMulticlass & cm);

   void initlpsolver();

   void initsvm();


   virtual bool evaluatefinishcriterion(const int32_t
         numberofsilpiterations);


   void addingweightsstep( const std::vector<float64_t> & curweights);

   float64_t getsumofsignfreealphas();

   float64_t getsquarenormofprimalcoefficients(
         const int32_t ind);

   virtual bool train_machine(CFeatures* data=NULL);

    virtual const char* get_name() const { return "MKLMulticlass"; }

protected:
   CGMNPSVM* svm;

   MKLMulticlassOptimizationBase* lpw;

   ::std::vector< std::vector< float64_t> > weightshistory;

   float64_t mkl_eps;

   int32_t max_num_mkl_iters;

   float64_t pnorm;

   std::vector<float64_t> normweightssquared;

   std::vector<float64_t> oldnormweightssquared;

   float64_t curalphaterm;
   float64_t oldalphaterm;
};

}
#endif // GMNPMKL_H_