www.pudn.com > svm_multiClass.rar > svm_learn.h
/***********************************************************************/
/* */
/* svm_learn.h */
/* */
/* Declarations for learning module of Support Vector Machine. */
/* */
/* Author: Thorsten Joachims */
/* Date: 02.07.02 */
/* */
/* Copyright (c) 2002 Thorsten Joachims - All rights reserved */
/* */
/* This software is available for non-commercial use only. It must */
/* not be modified and distributed without prior permission of the */
/* author. The author is not responsible for implications from the */
/* use of this software. */
/* */
/***********************************************************************/
#ifndef SVM_LEARN
#define SVM_LEARN
void svm_learn_classification(DOC **, double *, long, long, LEARN_PARM *,
KERNEL_PARM *, KERNEL_CACHE *, MODEL *,
double *);
void svm_learn_regression(DOC **, double *, long, long, LEARN_PARM *,
KERNEL_PARM *, KERNEL_CACHE **, MODEL *);
void svm_learn_ranking(DOC **, double *, long, long, LEARN_PARM *,
KERNEL_PARM *, KERNEL_CACHE **, MODEL *);
void svm_learn_optimization(DOC **, double *, long, long, LEARN_PARM *,
KERNEL_PARM *, KERNEL_CACHE *, MODEL *,
double *);
long optimize_to_convergence(DOC **, long *, long, long, LEARN_PARM *,
KERNEL_PARM *, KERNEL_CACHE *, SHRINK_STATE *,
MODEL *, long *, long *, double *,
double *, double *,
TIMING *, double *, long, long);
long optimize_to_convergence_sharedslack(DOC **, long *, long, long,
LEARN_PARM *,
KERNEL_PARM *, KERNEL_CACHE *, SHRINK_STATE *,
MODEL *, double *, double *, double *,
TIMING *, double *);
double compute_objective_function(double *, double *, double *, double,
long *, long *);
void clear_index(long *);
void add_to_index(long *, long);
long compute_index(long *,long, long *);
void optimize_svm(DOC **, long *, long *, long *, double, long *, long *,
MODEL *,
long, long *, long, double *, double *, double *,
LEARN_PARM *, CFLOAT *, KERNEL_PARM *, QP *, double *);
void compute_matrices_for_optimization(DOC **, long *, long *, long *, double,
long *,
long *, long *, MODEL *, double *,
double *, double *, long, long, LEARN_PARM *,
CFLOAT *, KERNEL_PARM *, QP *);
long calculate_svm_model(DOC **, long *, long *, double *, double *,
double *, double *, LEARN_PARM *, long *,
long *, MODEL *);
long check_optimality(MODEL *, long *, long *, double *, double *,
double *, long,
LEARN_PARM *,double *, double, long *, long *, long *,
long *, long, KERNEL_PARM *);
long check_optimality_sharedslack(DOC **docs, MODEL *model, long int *label,
double *a, double *lin, double *c, double *slack,
double *alphaslack, long int totdoc,
LEARN_PARM *learn_parm, double *maxdiff,
double epsilon_crit_org, long int *misclassified,
long int *active2dnum,
long int *last_suboptimal_at,
long int iteration, KERNEL_PARM *kernel_parm);
void compute_shared_slacks(DOC **docs, long int *label, double *a,
double *lin, double *c, long int *active2dnum,
LEARN_PARM *learn_parm,
double *slack, double *alphaslack);
long identify_inconsistent(double *, long *, long *, long, LEARN_PARM *,
long *, long *);
long identify_misclassified(double *, long *, long *, long,
MODEL *, long *, long *);
long identify_one_misclassified(double *, long *, long *, long,
MODEL *, long *, long *);
long incorporate_unlabeled_examples(MODEL *, long *,long *, long *,
double *, double *, long, double *,
long *, long *, long, KERNEL_PARM *,
LEARN_PARM *);
void update_linear_component(DOC **, long *, long *, double *, double *,
long *, long, long, KERNEL_PARM *,
KERNEL_CACHE *, double *,
CFLOAT *, double *);
long select_next_qp_subproblem_grad(long *, long *, double *,
double *, double *, long,
long, LEARN_PARM *, long *, long *,
long *, double *, long *, KERNEL_CACHE *,
long, long *, long *);
long select_next_qp_subproblem_rand(long *, long *, double *,
double *, double *, long,
long, LEARN_PARM *, long *, long *,
long *, double *, long *, KERNEL_CACHE *,
long *, long *, long);
long select_next_qp_slackset(DOC **docs, long int *label, double *a,
double *lin, double *slack, double *alphaslack,
double *c, LEARN_PARM *learn_parm,
long int *active2dnum, double *maxviol);
void select_top_n(double *, long, long *, long);
void init_shrink_state(SHRINK_STATE *, long, long);
void shrink_state_cleanup(SHRINK_STATE *);
long shrink_problem(DOC **, LEARN_PARM *, SHRINK_STATE *, KERNEL_PARM *,
long *, long *, long, long, long, double *, long *);
void reactivate_inactive_examples(long *, long *, double *, SHRINK_STATE *,
double *, double*, long, long, long, LEARN_PARM *,
long *, DOC **, KERNEL_PARM *,
KERNEL_CACHE *, MODEL *, CFLOAT *,
double *, double *);
/* cache kernel evalutations to improve speed */
KERNEL_CACHE *kernel_cache_init(long, long);
void kernel_cache_cleanup(KERNEL_CACHE *);
void get_kernel_row(KERNEL_CACHE *,DOC **, long, long, long *, CFLOAT *,
KERNEL_PARM *);
void cache_kernel_row(KERNEL_CACHE *,DOC **, long, KERNEL_PARM *);
void cache_multiple_kernel_rows(KERNEL_CACHE *,DOC **, long *, long,
KERNEL_PARM *);
void kernel_cache_shrink(KERNEL_CACHE *,long, long, long *);
void kernel_cache_reset_lru(KERNEL_CACHE *);
long kernel_cache_malloc(KERNEL_CACHE *);
void kernel_cache_free(KERNEL_CACHE *,long);
long kernel_cache_free_lru(KERNEL_CACHE *);
CFLOAT *kernel_cache_clean_and_malloc(KERNEL_CACHE *,long);
long kernel_cache_touch(KERNEL_CACHE *,long);
long kernel_cache_check(KERNEL_CACHE *,long);
long kernel_cache_space_available(KERNEL_CACHE *);
void compute_xa_estimates(MODEL *, long *, long *, long, DOC **,
double *, double *, KERNEL_PARM *,
LEARN_PARM *, double *, double *, double *);
double xa_estimate_error(MODEL *, long *, long *, long, DOC **,
double *, double *, KERNEL_PARM *,
LEARN_PARM *);
double xa_estimate_recall(MODEL *, long *, long *, long, DOC **,
double *, double *, KERNEL_PARM *,
LEARN_PARM *);
double xa_estimate_precision(MODEL *, long *, long *, long, DOC **,
double *, double *, KERNEL_PARM *,
LEARN_PARM *);
void avg_similarity_of_sv_of_one_class(MODEL *, DOC **, double *, long *, KERNEL_PARM *, double *, double *);
double most_similar_sv_of_same_class(MODEL *, DOC **, double *, long, long *, KERNEL_PARM *, LEARN_PARM *);
double distribute_alpha_t_greedily(long *, long, DOC **, double *, long, long *, KERNEL_PARM *, LEARN_PARM *, double);
double distribute_alpha_t_greedily_noindex(MODEL *, DOC **, double *, long, long *, KERNEL_PARM *, LEARN_PARM *, double);
void estimate_transduction_quality(MODEL *, long *, long *, long, DOC **, double *);
double estimate_margin_vcdim(MODEL *, double, double, KERNEL_PARM *);
double estimate_sphere(MODEL *, KERNEL_PARM *);
double estimate_r_delta_average(DOC **, long, KERNEL_PARM *);
double estimate_r_delta(DOC **, long, KERNEL_PARM *);
double length_of_longest_document_vector(DOC **, long, KERNEL_PARM *);
void write_model(char *, MODEL *);
void write_prediction(char *, MODEL *, double *, double *, long *, long *,
long, LEARN_PARM *);
void write_alphas(char *, double *, long *, long);
typedef struct cache_parm_s {
KERNEL_CACHE *kernel_cache;
CFLOAT *cache;
DOC **docs;
long m;
KERNEL_PARM *kernel_parm;
long offset,stepsize;
} cache_parm_t;
#endif