SubGradientLPM.h

Go to the documentation of this file.
00001 /*
00002  * This program is free software; you can redistribute it and/or modify
00003  * it under the terms of the GNU General Public License as published by
00004  * the Free Software Foundation; either version 3 of the License, or
00005  * (at your option) any later version.
00006  *
00007  * Written (W) 2007-2009 Soeren Sonnenburg
00008  * Written (W) 2007-2008 Vojtech Franc
00009  * Copyright (C) 2007-2009 Fraunhofer Institute FIRST and Max-Planck-Society
00010  */
00011 
00012 #ifndef _SUBGRADIENTLPM_H___
00013 #define _SUBGRADIENTLPM_H___
00014 
00015 #include <shogun/lib/config.h>
00016 
00017 #ifdef USE_CPLEX
00018 #include <shogun/lib/common.h>
00019 
00020 #include <shogun/mathematics/Cplex.h>
00021 
00022 #include <shogun/machine/LinearMachine.h>
00023 #include <shogun/features/Features.h>
00024 #include <shogun/features/Labels.h>
00025 
00026 namespace shogun
00027 {
00048 class CSubGradientLPM : public CLinearClassifier
00049 {
00050     public:
00051         CSubGradientLPM();
00052         CSubGradientLPM(
00053             float64_t C, CDotFeatures* traindat,
00054             CLabels* trainlab);
00055         virtual ~CSubGradientLPM();
00056 
00057         virtual inline EClassifierType get_classifier_type() { return CT_SUBGRADIENTLPM; }
00058 
00065         inline void set_C(float64_t c_neg, float64_t c_pos) { C1=c_neg; C2=c_pos; }
00066 
00067         inline float64_t get_C1() { return C1; }
00068         inline float64_t get_C2() { return C2; }
00069 
00070         inline void set_bias_enabled(bool enable_bias) { use_bias=enable_bias; }
00071         inline bool get_bias_enabled() { return use_bias; }
00072 
00073         inline void set_epsilon(float64_t eps) { epsilon=eps; }
00074         inline float64_t get_epsilon() { return epsilon; }
00075 
00076         inline void set_qpsize(int32_t q) { qpsize=q; }
00077         inline int32_t get_qpsize() { return qpsize; }
00078 
00079         inline void set_qpsize_max(int32_t q) { qpsize_max=q; }
00080         inline int32_t get_qpsize_max() { return qpsize_max; }
00081 
00082     protected:
00085         int32_t find_active(
00086             int32_t num_feat, int32_t num_vec, int32_t& num_active,
00087             int32_t& num_bound);
00088 
00091         void update_active(int32_t num_feat, int32_t num_vec);
00092 
00094         float64_t compute_objective(int32_t num_feat, int32_t num_vec);
00095 
00098         float64_t compute_min_subgradient(
00099             int32_t num_feat, int32_t num_vec, int32_t num_active,
00100             int32_t num_bound);
00101 
00103         float64_t line_search(int32_t num_feat, int32_t num_vec);
00104 
00106         void compute_projection(int32_t num_feat, int32_t num_vec);
00107 
00109         void update_projection(float64_t alpha, int32_t num_vec);
00110 
00112         void init(int32_t num_vec, int32_t num_feat);
00113 
00115         void cleanup();
00116 
00118         inline virtual const char* get_name() const { return "SubGradientLPM"; }
00119 
00120     protected:
00129         virtual bool train_machine(CFeatures* data=NULL);
00130 
00131     protected:
00132         float64_t C1;
00133         float64_t C2;
00134         float64_t epsilon;
00135         float64_t work_epsilon;
00136         float64_t autoselected_epsilon;
00137         int32_t qpsize;
00138         int32_t qpsize_max;
00139         int32_t qpsize_limit;
00140         bool use_bias;
00141 
00142         int32_t last_it_noimprovement;
00143         int32_t num_it_noimprovement;
00144 
00145         //idx vectors of length num_vec
00146         uint8_t* active; // 0=not active, 1=active, 2=on boundary
00147         uint8_t* old_active;
00148         int32_t* idx_active;
00149         int32_t* idx_bound;
00150         int32_t delta_active;
00151         int32_t delta_bound;
00152         float64_t* proj;
00153         float64_t* tmp_proj;
00154         int32_t* tmp_proj_idx;
00155 
00156         //vector of length num_feat
00157         float64_t* sum_CXy_active;
00158         float64_t* v;
00159         float64_t* old_v;
00160         float64_t sum_Cy_active;
00161 
00162         //vector of length num_feat
00163         int32_t pos_idx;
00164         int32_t neg_idx;
00165         int32_t zero_idx;
00166         int32_t* w_pos;
00167         int32_t* w_zero;
00168         int32_t* w_neg;
00169         float64_t* grad_w;
00170         float64_t grad_b;
00171         float64_t* grad_proj;
00172         float64_t* hinge_point;
00173         int32_t* hinge_idx;
00174 
00175         //vectors/sym matrix of size qpsize_limit
00176         float64_t* beta;
00177 
00178         CCplex* solver;
00179         float64_t lpmtim;
00180 };
00181 }
00182 #endif //USE_CPLEX
00183 #endif //_SUBGRADIENTLPM_H___
 All Classes Namespaces Files Functions Variables Typedefs Enumerations Enumerator Friends Defines

SHOGUN Machine Learning Toolbox - Documentation