www.pudn.com > TextClassify.rar > CLASSIFIERPARAM.H

// ClassifierParam.h: interface for the CClassifierParam class. 
// 
////////////////////////////////////////////////////////////////////// 
 
#if !defined(AFX_CLASSIFIERPARAM_H__2EB59D01_DED9_11D3_A70C_B0BCFB5CF9A2__INCLUDED_) 
#define AFX_CLASSIFIERPARAM_H__2EB59D01_DED9_11D3_A70C_B0BCFB5CF9A2__INCLUDED_ 
 
#if _MSC_VER > 1000 
#pragma once 
#endif // _MSC_VER > 1000 
 
class CClassifierParam   
{ 
public: 
	CClassifierParam(); 
	virtual ~CClassifierParam(); 
	void DumpToFile(CString strFileName); 
	bool GetFromFile(CString strFileName); 
private: 
	void Serialize(CArchive &ar); 
public:    //训练时需要使用的参数 
	CString m_txtTrainDir; 
	CString m_txtResultDir; 
	int		m_nFSMode;        //特征评估函数 
	int     m_nWordSize;      //特征数目 
	int     m_nSelMode;       //全局打分还是按类别打分计算特征的区分度 
	int     m_nOpMode;        //计算概率的方式 
	int     m_nLanguageType;  //文档的语种 
	BOOL    m_bStem;          //是否进行词干抽取 
	int     m_nWeightMode;    //特征加权的方法 
public:    //分类时需要使用的参数 
	int m_nClassifyType;              //0  单类分类; 1 多类分类 
	BOOL m_bEvaluation;               //是否需要对测试结果进行评价 
	BOOL m_bCopyFiles;                //是否将分好类的文件拷贝到结果目录下 
	CString m_strTestDir;             //测试文档或其所在的目录 
	CString m_strResultDir;           //测试结果所在的目录 
	CString m_strModelFile; 
	int m_nKNN;                       //KNN算法的k值 
	int m_nDocFormat;                 //测试文档的格式 
	double m_dThreshold;              //多类分类时使用的阈值 
	int m_nClassifierType;            //分类器的类型: -1 未知, 0 代表KNN, 1 代表SVM, 2 代表BAYES 
public: 
	void GetParamString(CString &strParam); 
	// calculation model 
	static const int nOpDocMode;      // based on document number model 
	static const int nOpWordMode;     // based on word number model 
	// feature evaluation fuction 
	static const int nFS_IGMode;      // Information gain feature selection 
	static const int nFS_MIMode;      // Mutual Informaiton feature selection 
	static const int nFS_CEMode;      // Cross Entropy for text feature selection 
	static const int nFS_X2Mode;      // X^2 Statistics feature selection 
	static const int nFS_WEMode;      // Weight of Evielence for text feature selection 
	static const int nFS_XXMode;      // Right half of IG 
	// how to select features 
	static const int nFSM_GolbalMode;  // 全局选 
	static const int nFSM_IndividualModel; // 单独选 
	// classifier type 
	static const int nCT_Unknown;     // Unknown 
	static const int nCT_KNN;         // KNN 
	static const int nCT_SVM;         // SVM 
	static const int nCT_BAYES;		  // BAYES 
	// document language type 
	static const int nLT_Chinese;     // Chinese 
	static const int nLT_English;     // English 
	// document format 
	static const int nDF_Directory;   // Directory 
	static const int nDF_Smart;       // Smart 
	// classify type 
	static const int nFT_Single;      // Single Classification 
	static const int nFT_Multi;       // Multiple Classification 
	// weight mode 
	static const int nWM_TF_IDF;      // TF*IDF 
	static const int nWM_TF_DIFF;     // TF*DIFF 
	static const int nWM_TF_IDF_DIFF; // TF*IDF*DIFF 
}; 
 
#endif // !defined(AFX_CLASSIFIERPARAM_H__2EB59D01_DED9_11D3_A70C_B0BCFB5CF9A2__INCLUDED_)