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  • #ifndef _LIBLINEAR_H
    #define _LIBLINEAR_H
    
    #define LIBLINEAR_VERSION 211
    
    #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 }; /* solver_type */
    
    struct parameter
    {
    	int solver_type;
    
    	/* these are for training only */
    	double eps;	        /* stopping criteria */
    	double C;
    	int nr_thread;
    	int nr_weight;
    	int *weight_label;
    	double* weight;
    	double p;
    	double *init_sol;
    	int max_iters;
    };
    
    struct model
    {
    	struct parameter param;
    	int nr_class;		/* number of classes */
    	int nr_feature;
    	double *w;
    	int *label;		/* label of each class */
    	double bias;
    };
    
    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_parameter_C(const struct problem *prob, const struct parameter *param, int nr_fold, double start_C, double max_C, double *best_C, double *best_rate);
    
    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);
    
    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);
    void set_print_string_function(void (*print_func) (const char*));
    
    #ifdef __cplusplus
    }
    #endif
    
    #endif /* _LIBLINEAR_H */