ilearner.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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#ifndef _LIBADABOOST_LEARNER_H_
#define _LIBADABOOST_LEARNER_H_

#include "LibAdaBoost/modules/Module.h"
#include "LibAdaBoost/modules/Publisher.h"
using namespace modules;

#include "LibAdaBoost/samples/learningsets/ILearningSet.h"
using namespace samples::learningsets;

#include "LibAdaBoost/classifiers/IClassifier.h"
using namespace classifiers;

#include <string>
using namespace std;

namespace learners{
	class IWeakLearner;

	class ILearner
		:public Module
		,public Publisher
	{
	public://Constructor & Destructor
		ILearner()
			:Publisher( "ILearner" )
			,Module()
		{
		}

		ILearner(const std::string &name)
			:Publisher( name )
			,Module()
		{
		}

		virtual ~ILearner(){};

	public://Module
		virtual std::string GetName(void) const = 0;
		std::string GetType(void) const {return "ILearner";}
		virtual void SetOptions(const modules::options::ModuleOptions &options) = 0;

	public:// ILearner
		virtual void Learn(void) = 0;
		virtual void Reset(void) = 0;

		virtual IClassifier *GetResult(void) = 0;
		
		virtual ILearningSet *GetLearningSet(void) = 0;
		virtual void SetLearningSet(ILearningSet *learningSet) = 0;

		virtual IWeakLearner *GetWeakLearner(void) = 0;
		virtual void SetWeakLearner(IWeakLearner *weakLearner) = 0;
	};
}

#endif