dependencies/third_party/libsvm/libsvm.h

+#ifndef _LIBSVM_H
+#define _LIBSVM_H
+
+namespace LIBSVM {
+    
+#define LIBSVM_VERSION 322
+    
+#ifdef __cplusplus
+    extern "C" {
+#endif
+        
+        extern int libsvm_version;
+        
+        struct svm_node
+        {
+            int index;
+            double value;
+        };
+        
+        struct svm_problem
+        {
+            int l;
+            double *y;
+            struct svm_node **x;
+        };
+        
+        enum { C_SVC, NU_SVC, ONE_CLASS, EPSILON_SVR, NU_SVR };	/* svm_type */
+        enum { LINEAR, POLY, RBF, SIGMOID, PRECOMPUTED }; /* kernel_type */
+        
+        struct svm_parameter
+        {
+            int svm_type;
+            int kernel_type;
+            int degree;	/* for poly */
+            double gamma;	/* for poly/rbf/sigmoid */
+            double coef0;	/* for poly/sigmoid */
+            
+            /* these are for training only */
+            double cache_size; /* in MB */
+            double eps;	/* stopping criteria */
+            double C;	/* for C_SVC, EPSILON_SVR and NU_SVR */
+            int nr_weight;		/* for C_SVC */
+            int *weight_label;	/* for C_SVC */
+            double* weight;		/* for C_SVC */
+            double nu;	/* for NU_SVC, ONE_CLASS, and NU_SVR */
+            double p;	/* for EPSILON_SVR */
+            int shrinking;	/* use the shrinking heuristics */
+            int probability; /* do probability estimates */
+        };
+        
+        //
+        // svm_model
+        //
+        struct svm_model
+        {
+            struct svm_parameter param;	/* parameter */
+            int nr_class;		/* number of classes, = 2 in regression/one class svm */
+            int l;			/* total #SV */
+            struct svm_node **SV;		/* SVs (SV[l]) */
+            double **sv_coef;	/* coefficients for SVs in decision functions (sv_coef[k-1][l]) */
+            double *rho;		/* constants in decision functions (rho[k*(k-1)/2]) */
+            double *probA;		/* pariwise probability information */
+            double *probB;
+            int *sv_indices;        /* sv_indices[0,...,nSV-1] are values in [1,...,num_traning_data] to indicate SVs in the training set */
+            
+            /* for classification only */
+            
+            int *label;		/* label of each class (label[k]) */
+            int *nSV;		/* number of SVs for each class (nSV[k]) */
+            /* nSV[0] + nSV[1] + ... + nSV[k-1] = l */
+            /* XXX */
+            int free_sv;		/* 1 if svm_model is created by svm_load_model*/
+            /* 0 if svm_model is created by svm_train */
+        };
+        
+        struct svm_model *svm_train(const struct svm_problem *prob, const struct svm_parameter *param);
+        void svm_cross_validation(const struct svm_problem *prob, const struct svm_parameter *param, int nr_fold, double *target);
+        
+        int svm_save_model(const char *model_file_name, const struct svm_model *model);
+        struct svm_model *svm_load_model(const char *model_file_name);
+        
+        int svm_get_svm_type(const struct svm_model *model);
+        int svm_get_nr_class(const struct svm_model *model);
+        void svm_get_labels(const struct svm_model *model, int *label);
+        void svm_get_sv_indices(const struct svm_model *model, int *sv_indices);
+        int svm_get_nr_sv(const struct svm_model *model);
+        double svm_get_svr_probability(const struct svm_model *model);
+        
+        double svm_predict_values(const struct svm_model *model, const struct svm_node *x, double* dec_values);
+        double svm_predict(const struct svm_model *model, const struct svm_node *x);
+        double svm_predict_probability(const struct svm_model *model, const struct svm_node *x, double* prob_estimates);
+        
+        void svm_free_model_content(struct svm_model *model_ptr);
+        void svm_free_and_destroy_model(struct svm_model **model_ptr_ptr);
+        void svm_destroy_param(struct svm_parameter *param);
+        
+        const char *svm_check_parameter(const struct svm_problem *prob, const struct svm_parameter *param);
+        int svm_check_probability_model(const struct svm_model *model);
+        
+        void svm_set_print_string_function(void (*print_func)(const char *));
+        
+#ifdef __cplusplus
+    }
+#endif
+    
+}
+
+#endif /* _LIBSVM_H */

xmm @ 68eae246

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