extern.h

计算机人工智能方面的决策树方法 c4.5

#ifndef _NEWSTAR_EXTERN_H_1999_12_23_11_24_34_OLDMOON_
#define _NEWSTAR_EXTERN_H_1999_12_23_11_24_34_OLDMOON_

#include "stdio.h"
#include "stdlib.h"
#include "string.h"

//Patched by oldmoon,99-12-23 上午 11:25:00
/*************************************************************************/
/*                                                                       */
/*              Global data for C4.5                                     */
/*              --------------------                                     */
/*                                                                       */
/*************************************************************************/


extern	int				MaxAtt,         /* max att number */
						MaxClass,       /* max class number */
						MaxDiscrVal;    /* max discrete values for any att */

extern  ItemNo			MaxItem;        /* max data item number */

extern  Description     *Item;          /* data items */

extern  DiscrValue      *MaxAttVal;     /* number of values for each att */

extern  char            *SpecialStatus; /* special att treatment */

extern  String          *ClassName,     /* class names */
						*AttName,       /* att names */
						**AttValName,   /* att value names */
						FileName;       /* family name of files */

extern  Boolean         AllKnown;       /* true if there have been no splits
										   on atts with missing values above
										   the current position in the tree */


/*************************************************************************/
/*                                                                       */
/*              Global parameters for C4.5                               */
/*              --------------------------                               */
/*                                                                       */
/*************************************************************************/


extern  int				VERBOSITY,      /* verbosity level (0 = none) */
						TRIALS;         /* number of trees to be grown */

extern  Boolean			GAINRATIO,      /* true=gain ratio, false=gain */
						SUBSET,         /* true if subset tests allowed */
						BATCH,          /* true if windowing turned off */
						UNSEENS,        /* true if to evaluate on test data */
						PROBTHRESH;     /* true if to use soft thresholds */

extern  ItemNo          MINOBJS,        /* minimum items each side of a cut */
						WINDOW,         /* initial window size */
						INCREMENT;      /* max window increment each iteration */

extern  double          CF;             /* confidence limit for tree pruning */


/************************************************************/
/*                  Function externs                        */
/************************************************************/
void	InitialiseTreeData();
void	InitialiseWeights();
Tree	FormTree(ItemNo Fp, ItemNo Lp);
void	PrintTree(Tree T);
void	SaveTree(Tree T, String Extension);
Tree	CopyTree(Tree T);
Boolean Prune(Tree T);
void	FormTarget(ItemNo Size);
void	FormInitialWindow();
Tree	Iterate(ItemNo Window, ItemNo IncExceptions);
void	Shuffle();
void	Swap(ItemNo a,ItemNo b);
ClassNo Category(Description CaseDesc, Tree DecisionTree);
int		TreeSize(Tree Node);
void    ReleaseTree(Tree Node);
void	PrintConfusionMatrix(ItemNo * ConfusionMat);
ItemCount CountItems(ItemNo Fp,ItemNo Lp);
Tree    Leaf(ItemCount *ClassFreq, ClassNo NodeClass, ItemCount Cases, ItemCount Errors);
void    EvalSubset(Attribute Att, ItemNo Fp, ItemNo Lp, ItemCount Items);
void	EvalDiscreteAtt(Attribute Att, ItemNo Fp, ItemNo Lp, ItemCount Items);
void    EvalContinuousAtt(Attribute Att, ItemNo Fp, ItemNo Lp);
double  Worth(double ThisInfo, double ThisGain, double MinGain);
void    SubsetTest(Tree Node, Attribute Att);
void    DiscreteTest(Tree Node, Attribute Att);
void	ContinTest(Tree Node, Attribute Att);
ItemNo  Group(DiscrValue V, ItemNo Fp, ItemNo Lp, Tree TestNode);
void    PrintHeader(char * Title);
int     getopt(int Argc, char **Argv, char *Str);
double  EstimateErrors(Tree T, ItemNo Fp, ItemNo Lp, int Sh, Boolean UpdateTree);
void    GetNames();
void	GetData(String Extension);
void	OneTree();
void    SoftenThresh(Tree T);
void	Evaluate(Boolean CMInfo, int Saved);
void	Classify(Description CaseDesc, Tree T, double Weight);
void    ResetFreq(DiscrValue MaxVal);
void    Quicksort(ItemNo Fp, ItemNo Lp, Attribute Att, void (*Exchange)(int,int));
double  TotalInfo(ItemCount V[], DiscrValue MinVal, DiscrValue MaxVal);
double  ComputeGain(double BaseInfo, double UnknFrac, DiscrValue MaxVal, ItemCount TotalItems);
void    PrintDistribution(Attribute Att, DiscrValue MaxVal,Boolean ShowNames);
void    Sprout(Tree Node, DiscrValue Branches);
double  GreatestValueBelow(Attribute Att, double t);
void	ComputeFrequencies(Attribute Att,ItemNo Fp,ItemNo Lp);
double	DiscrKnownBaseInfo(ItemCount KnownItems,DiscrValue MaxVal);
void    Error(int n, String s1, String s2);
Description GetDescription(FILE *Df);
Boolean ReadName(FILE *f, String s);
int		Which(String Val, String List[], int First, int Last);
String  CopyString(String x);
void    CheckPossibleValues(Tree T);
double AddErrs(ItemCount N, ItemCount e);
void    Indent(int Sh, char *Mark);
void    ScanTree(Tree T, ItemNo Fp, ItemNo Lp);
void    Combine(DiscrValue x, DiscrValue y, DiscrValue Last);
void    Uncombine(DiscrValue x, DiscrValue y);
void    PrintSubset(Attribute Att, Set Ss);
void    Show(Tree T,int  Sh);
int		MaxLine(Tree St);
void    ShowBranch(int Sh, Tree T, DiscrValue v);
void    OutTree(Tree T);
void    StreamOut(String s, int n);
void    StreamIn(String s,int n);

#endif