DomainAdaptationSVMLinear.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) 2007-2011 Christian Widmer
 * Copyright (C) 2007-2011 Max-Planck-Society
 */

#ifndef _DomainAdaptation_SVM_LINEAR_H___
#define _DomainAdaptation_SVM_LINEAR_H___

#include <shogun/lib/config.h>

#include <shogun/lib/common.h>
#include <shogun/classifier/svm/LibLinear.h>


namespace shogun
{

#ifdef HAVE_LAPACK

class CDomainAdaptationSVMLinear : public CLibLinear
{

    public:

        CDomainAdaptationSVMLinear();


        CDomainAdaptationSVMLinear(float64_t C, CDotFeatures* f, CLabels* lab, CLinearMachine* presvm, float64_t B);


        virtual ~CDomainAdaptationSVMLinear();


        void init(CLinearMachine* presvm, float64_t B);

        virtual EMachineType get_classifier_type() { return CT_DASVMLINEAR; }


        virtual CBinaryLabels* apply_binary(CFeatures* data=NULL);


        virtual CLinearMachine* get_presvm();


        virtual float64_t get_B();


        virtual float64_t get_train_factor();


        virtual void set_train_factor(float64_t factor);

        //virtual std::vector<float64_t> get_linear_term();


        /*
         * set linear term of the QP
         *
         * @param lin the linear term
         */
        //virtual void set_linear_term(std::vector<float64_t> lin);


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

    protected:

        virtual bool is_presvm_sane();

        virtual bool train_machine(CFeatures* data=NULL);

    protected:

        CLinearMachine* presvm;


        float64_t B;


        float64_t train_factor;


};
#endif //HAVE_LAPACK

} /* namespace shogun  */

#endif //_DomainAdaptation_SVM_LINEAR_H___