MulticlassLogisticRegression.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 Sergey Lisitsyn
 * Copyright (C) 2012 Sergey Lisitsyn
 */
 
#ifndef MULTICLASSLOGISTICREGRESSION_H_
#define MULTICLASSLOGISTICREGRESSION_H_
#include <shogun/lib/config.h>
#include <shogun/lib/common.h>
#include <shogun/features/DotFeatures.h>
#include <shogun/machine/LinearMulticlassMachine.h>
 
#include <shogun/multiclass/MulticlassOneVsRestStrategy.h>
#include <shogun/io/SGIO.h>
#include <shogun/mathematics/Math.h>
#include <shogun/labels/MulticlassLabels.h>
#include <shogun/lib/slep/slep_mc_plain_lr.h>
 
#include <vector>
 
using std::vector;
#include <Eigen/Dense>
#include <shogun/base/some.h>                                                                       
 
namespace shogun
{
 
    class CMulticlassLogisticRegression : public CLinearMulticlassMachine
    {
        public:
        
            MACHINE_PROBLEM_TYPE(PT_MULTICLASS)
 
            
            CMulticlassLogisticRegression();
 
            CMulticlassLogisticRegression(float64_t z, CDotFeatures* feats, CLabels* labs);
 
            ~CMulticlassLogisticRegression();
 
            virtual const char* get_name() const;
 
            void set_z(float64_t z);
        
            inline float64_t get_z() const;
 
            void set_epsilon(float64_t epsilon);
        
            float64_t get_epsilon() const;
 
            void set_max_iter(int32_t max_iter);
        
            inline int32_t get_max_iter() const;
                
            vector<SGVector<float64_t>> get_w();
            void set_w(vector<Eigen::VectorXd>& wnew);
 
            vector<float64_t> get_bias();
 
        protected:
 
            virtual bool train_machine(CFeatures* data = NULL);
 
    private:
 
            void init_defaults();
 
            void register_parameters();
 
    protected:
 
            float64_t m_z;
 
            float64_t m_epsilon;
 
            int32_t m_max_iter;
 
    };
}
#endif