adaboostlearner.h

WeakLearner,弱分类器

//LAB_LicenseBegin==============================================================
//  Copyright (c) 2005-2006, Hicham GHORAYEB < [e-mail] >
//  All rights reserved.
//
//	This software is a Library for Adaptive Boosting. It provides a generic 
//	framework for the study of the Boosting algorithms. The framework provides 
//	the different tasks for boosting: Learning, Validation, Test, Profiling and 
//	Performance Analysis Tasks.
//
//	This Library was developped during my PhD studies at:
//	Ecole des Mines de Paris - Centre de Robotique( CAOR )
//	http://caor.ensmp.fr
//	under the supervision of Pr. Claude Laurgeau and Bruno Steux
//
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//================================================================LAB_LicenseEnd
#ifndef _LIBADABOOST_ADABOOST_LEARNER_H_
#define _LIBADABOOST_ADABOOST_LEARNER_H_

#include "LibAdaBoost/modules/ModuleFactoryBase.h"
using namespace modules;

#include "LibAdaBoost/samples/learningsets/ILearningSet.h"
#include "LibAdaBoost/classifiers/WeightedSumClassifier.h"
#include "LibAdaBoost/learners/ILearner.h"
#include "LibAdaBoost/learners/IWeakLearner.h"

using namespace samples::learningsets;
using namespace classifiers;
using namespace classifiers::features;

namespace learners{
	class AdaBoostLearner: public ILearner
	{
	public:
		AdaBoostLearner();
		AdaBoostLearner(ILearningSet *learningSet);
		AdaBoostLearner(ILearningSet *learningSet, IWeakLearner *weakLearner);

		virtual ~AdaBoostLearner();

		void SetNbrCycles(int nbr){ m_NbrCycles = nbr;}
		int GetNbrCycles(void) const{ return m_NbrCycles;}

	public://Module
		std::string GetName(void) const { return "AdaBoostLearner";};
		void SetOptions(const modules::options::ModuleOptions &options);

	public:// ILearner
		virtual void Learn(void);
		virtual void Reset(void);

		virtual IClassifier *GetResult(void);

		virtual ILearningSet *GetLearningSet(void);
		virtual void SetLearningSet(ILearningSet *learningSet);

		virtual IWeakLearner *GetWeakLearner(void);
		virtual void SetWeakLearner(IWeakLearner *weakLearner);

	protected:
		WeightedSumClassifier *m_wsClassifier;

		int m_NbrCycles;
		double m_err;

		ILearningSet *m_LearningSet;

		IWeakLearner *m_WeakLearner;
	};

	typedef ModuleFactory<AdaBoostLearner> AdaBoostLearnerFactory;
}
#endif