svm_common.h

支持向量基预测的小数据量的预测方法。包括数据拟合

#if !defined(AFX_TEST_H__B678A414_54CC_480B_8068_4FAEED66F002__INCLUDED_)
#define AFX_TEST_H__B678A414_54CC_480B_8068_4FAEED66F002__INCLUDED_

#if _MSC_VER > 1000
#pragma once
#endif // _MSC_VER > 1000
/* # define MICROSOFT */

# include <stdio.h>
# include <ctype.h>
# include <math.h>
# include <string.h>
# include <stdlib.h>
# include <time.h> 
# include <float.h>

# define VERSION       "V3.50"
# define VERSION_DATE  "01.11.00"

# define CFLOAT  float       /* the type of float to use for caching */
/* kernel evaluations. Using float saves */
/* us some memory, but you can use double, too */
# define FNUM    long        /* the type used for storing feature ids */
# define FVAL    float       /* the type used for storing feature values */

# define LINEAR  0           /* linear kernel type */
# define POLY    1           /* polynoial kernel type */
# define RBF     2           /* rbf kernel type */
# define SIGMOID 3           /* sigmoid kernel type */
# define CUSTOM  4


typedef struct word
{
	FNUM    wnum;	
	FVAL    weight;
} SVM_WORD;

typedef struct doc
{
	long    docnum;
	double  twonorm_sq;
	SVM_WORD    *words;
} DOC;

typedef struct learn_parm 
{
	double svm_c;                /* upper bound C on alphas */
	double svm_costratio;        /* factor to multiply C for positive examples */
	double transduction_posratio;/* fraction of unlabeled examples to be */	/* classified as positives */
	long   biased_hyperplane;    /* if nonzero, use hyperplane w*x+b=0 	otherwise w*x=0 */
	long   svm_maxqpsize;        /* size q of working set */
	long   svm_newvarsinqp;      /* new variables to enter the working set in each iteration */
	double epsilon_crit;         /* tolerable error for distances used in stopping criterion */
	double epsilon_shrink;       /* how much a multiplier should be above  zero for shrinking */
	long   svm_iter_to_shrink;   /* iterations h after which an example can be removed by shrinking */
	long   remove_inconsistent;  /* exclude examples with alpha at C and  retrain */
	
								 
	long   skip_final_opt_check; 
								 /* do not check KT-Conditions at the end of optimization for examples removed by  
								 shrinking. WARNING: This might lead to sub-optimal solutions! */
	
	long   compute_loo;          /* if nonzero, computes leave-one-out	 estimates */
	double rho;                  /* parameter in xi/alpha-estimates and for pruning leave-one-out range [1..2] */
	long   xa_depth;             /* parameter in xi/alpha-estimates upper  bounding the number of SV the current alpha_t is distributed over */
	char predfile[200];          /* file for predicitions on unlabeled examples					 in transduction */
	char alphafile[200];         
								/* file to store optimal alphas in. use
									empty string if alphas should not be 	 output */
	
	
	/* you probably do not want to touch the following */
	double epsilon_const;        /* tolerable error on eq-constraint */
	double epsilon_a;            /* tolerable error on alphas at bounds */
	double opt_precision;        /* precision of solver, set to e.g. 1e-21 	 if you get convergence problems */
	
	
	/* the following are only for internal use */
	long   svm_c_steps;          /* do so many steps for finding optimal C */
	double svm_c_factor;         /* increase C by this factor every step */
	double svm_costratio_unlab;
	double svm_unlabbound;
	double *svm_cost;            /* individual upper bounds for each var */
	long   totwords;             /* number of features */
} LEARN_PARM;

typedef struct kernel_parm 
{
	long    kernel_type;   
	long    poly_degree;
	double  rbf_gamma;
	double  coef_lin;
	double  coef_const;
	char    custom[50];    /* for user supplied kernel */
} KERNEL_PARM;

typedef struct model 
{
	long    sv_num;	
	long    at_upper_bound;
	double  b;
	DOC     **supvec;
	double  *alpha;
	long    *index;       /* index from docnum to position in model */
	long    totwords;     /* number of features */
	long    totdoc;       /* number of training documents */
	KERNEL_PARM kernel_parm; /* kernel */
	
	/* the following values are not written to file */
	double  loo_error,loo_recall,loo_precision; /* leave-one-out estimates */
	double  xa_error,xa_recall,xa_precision;    /* xi/alpha estimates */
												double  *lin_weights;  	/* weights for linear case using folding */
} MODEL;

typedef struct quadratic_program 
{
	long   opt_n;            /* number of variables */
	long   opt_m;            /* number of linear equality constraints */
	double *opt_ce,*opt_ce0; /* linear equality constraints */
	double *opt_g;           /* hessian of objective */
	double *opt_g0;          /* linear part of objective */
	double *opt_xinit;       /* initial value for variables */
	double *opt_low,*opt_up; /* box constraints */
} QP;

typedef struct kernel_cache 
{
	long   *index;  /* cache some kernel evalutations */
	CFLOAT *buffer; /* to improve speed */
	long   *invindex;
	long   *active2totdoc;
	long   *totdoc2active;
	long   *lru;
	long   *occu;
	long   elems;
	long   max_elems;
	long   time;
	long   activenum;
	long   buffsize;
} KERNEL_CACHE;

 
typedef struct timing_profile 
{
	long   time_kernel;
	long   time_opti;
	long   time_shrink;
	long   time_update;
	long   time_model;
	long   time_check;
	long   time_select;
} TIMING;
 
typedef struct shrink_state 
{
	long   *active;
	long   *inactive_since;
	long   deactnum;
	double **a_history;
} SHRINK_STATE;


double classify_example(MODEL *, DOC *);
double classify_example_linear(MODEL *, DOC *);
CFLOAT kernel(KERNEL_PARM *, DOC *, DOC *); 
double custom_kernel(KERNEL_PARM *, DOC *, DOC *); 
double sprod_ss(SVM_WORD *, SVM_WORD *);
double model_length_s(MODEL *, KERNEL_PARM *);
void   clear_vector_n(double *, long);
void   add_vector_ns(double *, SVM_WORD *, double);
double sprod_ns(double *, SVM_WORD *);
void   add_weight_vector_to_linear_model(MODEL *);
int    read_model(char *, MODEL *, long, long);
int    read_documents(char *, DOC *, long *, long, long, long *, long *);
int    parse_document(char *, DOC *, long *, long *, long);
int    nol_ll(char *, long *, long *, long *);
long   minl(long, long);
long   maxl(long, long);
long   get_runtime();
void   *my_malloc(long); 
void   copyright_notice();
double custom_kernel(KERNEL_PARM *kernel_parm,DOC *a,DOC*b);
void  SetInitParam();
int isnan(double);

//chen Longbin
void	printm(char* str);
void    printe(char* str);

#endif // !defined(AFX_TEST_H__B678A414_54CC_480B_8068_4FAEED66F002__INCLUDED_)