/***********************************************************************/ /* */ /* 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