adaboost.h

AdaBoost is an efficient tool in machine learning. It can combine a series of weak learners into a s

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 File: adaboost.h                                                                         
 Authors: Yao Wei  
 Date Created    : 2007-8-11
                                          
****************************************************************************/

#ifndef ADA_BOOST_H
#define ADA_BOOST_H

#include "WeakLearner.h"
#include "mex.h"

class Boosting  
{
private:
	int n_samples;         //number of train sample
	int n_input;            //dimension of each sample
	int max_iter;       //max number of boost step
	WeakLearner *leaner;   //all weaker leaner
	
	//information of train set contains: #class, #each class and each class item
	//that is to say, if we have label={1,1,2,6,4,1,4,4,6,1,6,2,1,1,1,4,4}; we will get 
    //# class: count=4
	//concrete label:      eachlabel={1,2,6,4}
	//each count of label: eachcount={7,2,3,5} 
	struct taginfo
	{
		taginfo()
		{
			count = 0;
			eachlabel = 0;
			eachcount = 0;
		}
		int count;                   //class count;
		int *eachcount;              //each class's count
		double *eachlabel;           //store all label
	}info;

	Mat *submat;    //sub-sample correspond to each class


public:
	//matlab interface of boosting train
	void mexTrain(int nlhs, mxArray *plhs[],
		int nrhs, const mxArray *prhs[]);

	//matlab interface of boosting predict
	void mexPredict(int nlhs, mxArray *plhs[],
		int nrhs, const mxArray *prhs[]);

	Boosting();    //Construction

	virtual ~Boosting();

private:
	// free memory
	void Free();

	//predict a sample using majority voting
	double Vote(double *feature,int n_input);
	
	//set iteration of Boosting
	void SetIteration(int _max_iter){max_iter = _max_iter;}

	//train Multi-Class Boosting
	void DoTrain(); 
	
	//train Boosting 1 vs 1
	WeakLearner TrainOneVsOne
		(const Mat &mat1,const Mat &mat2,double label1,double label2);
	
	//get information of train data
	void GetClassInfo(const Vec &responses);
	
	//preprocess train data
	void Preprocess(const Mat &train,const Vec &responses);
	
	//unroll data according to each class label
	void UnrollData(const Mat &train,const Vec &responses);
	
};

#endif //ADA_BOOST_H