First commit

liblinear-2.49/linear.h

@@ -0,0 +1,90 @@
+#include <stdbool.h>
+#ifndef _LIBLINEAR_H
+#define _LIBLINEAR_H
+
+#define LIBLINEAR_VERSION 249
+
+#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;
+	bool w_recalc;		/* for -s 1, 3; may be extended to -s 12, 13, 21 */
+};
+
+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 */
+