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linear.h
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linear.h
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#ifndef _LIBLINEAR_H
#define _LIBLINEAR_H
#define LIBLINEAR_VERSION 247
#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 */