svm.h
/*
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#pragma once
#define LIBSVM_VERSION 311
#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;
};
struct svm_scaling {
// index = 1 if usable, index = 0 if not
struct svm_node* obj;
// max features scaled
int max;
svm_scaling() : max(0) {}
};
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;
/* 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 */
/* for scaling */
struct svm_node* scaling;
};
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);
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
svm_model
Definition: svm.h:99
svm_model::rho
double * rho
Definition: svm.h:107
svm_model::nSV
int * nSV
Definition: svm.h:114
svm_model::free_sv
int free_sv
Definition: svm.h:117
svm_model::nr_class
int nr_class
Definition: svm.h:102
svm_model::scaling
struct svm_node * scaling
Definition: svm.h:122
svm_model::probB
double * probB
Definition: svm.h:109
svm_model::param
struct svm_parameter param
Definition: svm.h:101
svm_model::SV
struct svm_node ** SV
Definition: svm.h:105
svm_model::sv_coef
double ** sv_coef
Definition: svm.h:106
svm_model::l
int l
Definition: svm.h:103
svm_model::label
int * label
Definition: svm.h:113
svm_model::probA
double * probA
Definition: svm.h:108
svm_node
Definition: svm.h:49
svm_node::value
double value
Definition: svm.h:51
svm_node::index
int index
Definition: svm.h:50
svm_parameter
Definition: svm.h:75
svm_parameter::cache_size
double cache_size
Definition: svm.h:83
svm_parameter::weight_label
int * weight_label
Definition: svm.h:87
svm_parameter::eps
double eps
Definition: svm.h:84
svm_parameter::coef0
double coef0
Definition: svm.h:80
svm_parameter::svm_type
int svm_type
Definition: svm.h:76
svm_parameter::p
double p
Definition: svm.h:90
svm_parameter::kernel_type
int kernel_type
Definition: svm.h:77
svm_parameter::nr_weight
int nr_weight
Definition: svm.h:86
svm_parameter::nu
double nu
Definition: svm.h:89
svm_parameter::gamma
double gamma
Definition: svm.h:79
svm_parameter::C
double C
Definition: svm.h:85
svm_parameter::probability
int probability
Definition: svm.h:92
svm_parameter::shrinking
int shrinking
Definition: svm.h:91
svm_parameter::degree
int degree
Definition: svm.h:78
svm_parameter::weight
double * weight
Definition: svm.h:88
svm_problem
Definition: svm.h:54
svm_problem::l
int l
Definition: svm.h:55
svm_problem::y
double * y
Definition: svm.h:56
svm_problem::x
struct svm_node ** x
Definition: svm.h:58
svm_scaling
Definition: svm.h:61
svm_scaling::obj
struct svm_node * obj
Definition: svm.h:64
svm_scaling::max
int max
Definition: svm.h:67
svm_scaling::svm_scaling
svm_scaling()
Definition: svm.h:69