SVMOcas.h

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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 Vojtech Franc
00008  * Written (W) 2007-2009 Soeren Sonnenburg
00009  * Copyright (C) 2007-2009 Fraunhofer Institute FIRST and Max-Planck-Society
00010  */
00011 
00012 #ifndef _SVMOCAS_H___
00013 #define _SVMOCAS_H___
00014 
00015 #include <shogun/lib/common.h>
00016 #include <shogun/machine/LinearMachine.h>
00017 #include <shogun/lib/external/libocas.h>
00018 #include <shogun/features/DotFeatures.h>
00019 #include <shogun/labels/Labels.h>
00020 
00021 namespace shogun
00022 {
00023 #ifndef DOXYGEN_SHOULD_SKIP_THIS
00024 enum E_SVM_TYPE
00025 {
00026     SVM_OCAS = 0,
00027     SVM_BMRM = 1
00028 };
00029 #endif
00030 
00032 class CSVMOcas : public CLinearMachine
00033 {
00034     public:
00035 
00037         MACHINE_PROBLEM_TYPE(PT_BINARY);
00038 
00040         CSVMOcas();
00041 
00046         CSVMOcas(E_SVM_TYPE type);
00047 
00054         CSVMOcas(
00055             float64_t C, CDotFeatures* traindat,
00056             CLabels* trainlab);
00057         virtual ~CSVMOcas();
00058 
00063         virtual EMachineType get_classifier_type() { return CT_SVMOCAS; }
00064 
00071         inline void set_C(float64_t c_neg, float64_t c_pos) { C1=c_neg; C2=c_pos; }
00072 
00077         inline float64_t get_C1() { return C1; }
00078 
00083         inline float64_t get_C2() { return C2; }
00084 
00089         inline void set_epsilon(float64_t eps) { epsilon=eps; }
00090 
00095         inline float64_t get_epsilon() { return epsilon; }
00096 
00101         inline void set_bias_enabled(bool enable_bias) { use_bias=enable_bias; }
00102 
00107         inline bool get_bias_enabled() { return use_bias; }
00108 
00113         inline void set_bufsize(int32_t sz) { bufsize=sz; }
00114 
00119         inline int32_t get_bufsize() { return bufsize; }
00120 
00125         virtual float64_t compute_primal_objective() const;
00126 
00127     protected:
00136         static void compute_W(
00137             float64_t *sq_norm_W, float64_t *dp_WoldW, float64_t *alpha,
00138             uint32_t nSel, void* ptr);
00139 
00146         static float64_t update_W(float64_t t, void* ptr );
00147 
00156         static int add_new_cut(
00157             float64_t *new_col_H, uint32_t *new_cut, uint32_t cut_length,
00158             uint32_t nSel, void* ptr );
00159 
00165         static int compute_output( float64_t *output, void* ptr );
00166 
00173         static int sort( float64_t* vals, float64_t* data, uint32_t size);
00174 
00176         static inline void print(ocas_return_value_T value)
00177         {
00178               return;
00179         }
00180 
00181     protected:
00190         virtual bool train_machine(CFeatures* data=NULL);
00191 
00193         inline const char* get_name() const { return "SVMOcas"; }
00194     private:
00195         void init();
00196 
00197     protected:
00199         bool use_bias;
00201         int32_t bufsize;
00203         float64_t C1;
00205         float64_t C2;
00207         float64_t epsilon;
00209         E_SVM_TYPE method;
00210 
00212         float64_t* old_w;
00214         float64_t old_bias;
00216         float64_t* tmp_a_buf;
00218         SGVector<float64_t> lab;
00219 
00222         float64_t** cp_value;
00224         uint32_t** cp_index;
00226         uint32_t* cp_nz_dims;
00228         float64_t* cp_bias;
00229         
00231         float64_t primal_objective;
00232 };
00233 }
00234 #endif
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