NewtonSVM.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) 2012 Harshit Syal
 * Copyright (C) 2012 Harshit Syal
 */

#ifndef _NEWTONSVM_H___
#define _NEWTONSVM_H___

#include <shogun/lib/common.h>
#include <shogun/machine/LinearMachine.h>
#include <shogun/features/DotFeatures.h>
#include <shogun/labels/Labels.h>

namespace shogun
{
#ifdef HAVE_LAPACK

class CNewtonSVM : public CLinearMachine
{
    public:
        MACHINE_PROBLEM_TYPE(PT_BINARY);

        CNewtonSVM();

        CNewtonSVM(float64_t C, CDotFeatures* traindat, CLabels* trainlab, int32_t itr=20);
        
        virtual ~CNewtonSVM();

        virtual inline EMachineType get_classifier_type() { return CT_NEWTONSVM; }

        inline void set_C(float64_t c) { C=c; }

        inline float64_t get_epsilon() { return epsilon; }

        inline void set_epsilon(float64_t e) { epsilon=e; }

        inline float64_t get_C() { return C; }

        
        inline void set_bias_enabled(bool enable_bias) { use_bias=enable_bias; }

        inline bool get_bias_enabled() { return use_bias; }

        inline int32_t get_num_iter() {return num_iter;}

        inline void set_num_iter(int32_t iter) { num_iter=iter; }
        
        inline virtual const char* get_name() const { return "NewtonSVM"; }
    
    protected:
        virtual bool train_machine(CFeatures* data=NULL);

    private:
        void obj_fun_linear(float64_t* weights, float64_t* out, float64_t* obj,
                int32_t* sv, int32_t* numsv, float64_t* grad);

        void line_search_linear(float64_t* weights, float64_t* d,
                float64_t* out, float64_t* tx);

    protected:
        float64_t lambda, C, epsilon;
        float64_t prec;
        int32_t x_n, x_d, num_iter;

        bool use_bias;
};
#endif //HAVE_LAPACK
}
#endif //_NEWTONSVM_H___