adaboost_ecoc.h

C＋＋编写的机器学习算法 Lemga is a C++ package which consists of classes for several learning models and gener

// -*- C++ -*-
#ifndef __LEMGA_MULTICLASS_ADABOOST_ECOC_H__
#define __LEMGA_MULTICLASS_ADABOOST_ECOC_H__

/** @file
 *  @brief Declare @link lemga::AdaBoost_ECOC AdaBoost_ECOC@endlink class.
 *
 *  $Id: adaboost_ecoc.h 2541 2006-01-10 06:02:27Z ling $
 */

#include "multiclass_ecoc.h"
#include "shared_ptr.h"

namespace lemga {

typedef std::vector<DataWgt> JointWgt;
typedef const_shared_ptr<JointWgt> pJointWgt;

/** @brief AdaBoost.ECC with exponential cost and Hamming distance.
 */
class AdaBoost_ECOC : public MultiClass_ECOC {
public:
    enum PARTITION_METHOD {
        RANDOM_HALF,
        MAX_CUT,
        MAX_CUT_GREEDY
    };

protected:
    PARTITION_METHOD par_method;

public:
    AdaBoost_ECOC () : MultiClass_ECOC(), par_method(MAX_CUT_GREEDY) {}
    explicit AdaBoost_ECOC (std::istream& is) { is >> *this; }

    virtual const id_t& id () const;
    virtual AdaBoost_ECOC* create () const { return new AdaBoost_ECOC(); }
    virtual AdaBoost_ECOC* clone () const {
        return new AdaBoost_ECOC(*this); }

    void set_partition_method (PARTITION_METHOD m) { par_method = m; }

protected:
    // only valid during training
    JointWgt joint_wgt;
    std::vector<bool> cur_err;
    pDataWgt cur_smpwgt;
    pDataWgt smpwgt_with_partition (const ECOC_VECTOR&);

    virtual void reset_training ();
    virtual bool ECOC_partition (UINT, ECOC_VECTOR&);
    virtual pLearnModel train_with_partition (ECOC_VECTOR&);
    virtual REAL assign_weight (const ECOC_VECTOR&, const LearnModel&);
    virtual void update_training (const ECOC_VECTOR&);

    std::vector<std::vector<REAL> > confusion_matrix () const;
    ECOC_VECTOR max_cut (UINT) const;
    ECOC_VECTOR max_cut_greedy (UINT) const;
    ECOC_VECTOR random_half (UINT) const;
};

} // namespace lemga

#ifdef  __ADABOOST_ECOC_H__
#warning "This header file may conflict with another `adaboost_ecoc.h' file."
#endif
#define __ADABOOST_ECOC_H__
#endif