#ifndef _LIBLINEAR_H #define _LIBLINEAR_H #define LIBLINEAR_VERSION 246 #ifdef __cplusplus extern "C" { #endif extern int liblinear_version; struct feature_node { int index; double value; }; struct problem { int l, n; double *y; struct feature_node **x; double bias; /* < 0 if no bias term */ }; enum { L2R_LR, L2R_L2LOSS_SVC_DUAL, L2R_L2LOSS_SVC, L2R_L1LOSS_SVC_DUAL, MCSVM_CS, L1R_L2LOSS_SVC, L1R_LR, L2R_LR_DUAL, L2R_L2LOSS_SVR = 11, L2R_L2LOSS_SVR_DUAL, L2R_L1LOSS_SVR_DUAL, ONECLASS_SVM = 21 }; /* solver_type */ struct parameter { int solver_type; /* these are for training only */ double eps; /* stopping tolerance */ double C; int nr_weight; int *weight_label; double* weight; double p; double nu; double *init_sol; int regularize_bias; }; struct model { struct parameter param; int nr_class; /* number of classes */ int nr_feature; double *w; int *label; /* label of each class */ double bias; double rho; /* one-class SVM only */ }; struct model* train(const struct problem *prob, const struct parameter *param); void cross_validation(const struct problem *prob, const struct parameter *param, int nr_fold, double *target); void find_parameters(const struct problem *prob, const struct parameter *param, int nr_fold, double start_C, double start_p, double *best_C, double *best_p, double *best_score); double predict_values(const struct model *model_, const struct feature_node *x, double* dec_values); double predict(const struct model *model_, const struct feature_node *x); double predict_probability(const struct model *model_, const struct feature_node *x, double* prob_estimates); int save_model(const char *model_file_name, const struct model *model_); struct model *load_model(const char *model_file_name); int get_nr_feature(const struct model *model_); int get_nr_class(const struct model *model_); void get_labels(const struct model *model_, int* label); double get_decfun_coef(const struct model *model_, int feat_idx, int label_idx); double get_decfun_bias(const struct model *model_, int label_idx); double get_decfun_rho(const struct model *model_); void free_model_content(struct model *model_ptr); void free_and_destroy_model(struct model **model_ptr_ptr); void destroy_param(struct parameter *param); const char *check_parameter(const struct problem *prob, const struct parameter *param); int check_probability_model(const struct model *model); int check_regression_model(const struct model *model); int check_oneclass_model(const struct model *model); void set_print_string_function(void (*print_func) (const char*)); #ifdef __cplusplus } #endif #endif /* _LIBLINEAR_H */