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
 */

#ifndef MKLMULTICLASS_H_
#define MKLMULTICLASS_H_

#include <vector>

#include <shogun/base/SGObject.h>
#include <shogun/kernel/Kernel.h>  
#include <shogun/kernel/CombinedKernel.h> 
#include <shogun/classifier/svm/GMNPSVM.h>
#include <shogun/classifier/mkl/MKLMultiClassGLPK.h>
#include <shogun/classifier/mkl/MKLMultiClassGradient.h>


namespace shogun
{
class CMKLMultiClass : public CMultiClassSVM
{
public:
    CMKLMultiClass();
    CMKLMultiClass(float64_t C, CKernel* k, CLabels* lab);


    virtual ~CMKLMultiClass();

    virtual inline EClassifierType 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);
    

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;
    
};
}
#endif // GMNPMKL_H_