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celeste/svm.cpp File Reference

#include <math.h>
#include <stdio.h>
#include <stdlib.h>
#include <ctype.h>
#include <float.h>
#include <string.h>
#include <stdarg.h>
#include <locale.h>
#include "svm.h"

Include dependency graph for svm.cpp:

Include dependency graph

Classes

class  Cache
struct  Cache::head_t
class  QMatrix
class  Kernel
class  Solver
struct  Solver::SolutionInfo
class  Solver_NU
class  SVC_Q
class  ONE_CLASS_Q
class  SVR_Q
struct  decision_function
struct  svm_model

Defines

#define INF   HUGE_VAL
#define TAU   1e-12
#define Malloc(type, n)   (type *)malloc((n)*sizeof(type))

Typedefs

typedef float Qfloat
typedef signed char schar

Functions

template<class T>
min (T x, T y)
template<class T>
max (T x, T y)
template<class T>
void swap (T &x, T &y)
template<class S, class T>
void clone (T *&dst, S *src, int n)
double powi (double base, int times)
void info (const char *fmt,...)
void info_flush ()
decision_function svm_train_one (const svm_problem *prob, const svm_parameter *param, double Cp, double Cn)
void sigmoid_train (int l, const double *dec_values, const double *labels, double &A, double &B)
double sigmoid_predict (double decision_value, double A, double B)
void multiclass_probability (int k, double **r, double *p)
void svm_binary_svc_probability (const svm_problem *prob, const svm_parameter *param, double Cp, double Cn, double &probA, double &probB)
double svm_svr_probability (const svm_problem *prob, const svm_parameter *param)
void svm_group_classes (const svm_problem *prob, int *nr_class_ret, int **label_ret, int **start_ret, int **count_ret, int *perm)
svm_modelsvm_train (const svm_problem *prob, const svm_parameter *param)
void svm_cross_validation (const svm_problem *prob, const svm_parameter *param, int nr_fold, double *target)
int svm_get_svm_type (const svm_model *model)
int svm_get_nr_class (const svm_model *model)
void svm_get_labels (const svm_model *model, int *label)
double svm_get_svr_probability (const svm_model *model)
void svm_predict_values (const svm_model *model, const svm_node *x, double *dec_values)
double svm_predict (const svm_model *model, const svm_node *x)
double svm_predict_probability (const svm_model *model, const svm_node *x, double *prob_estimates)
int svm_save_model (const char *model_file_name, const svm_model *model)
svm_modelsvm_load_model (const char *model_file_name)
void svm_destroy_model (svm_model *model)
void svm_destroy_param (svm_parameter *param)
const char * svm_check_parameter (const svm_problem *prob, const svm_parameter *param)
int svm_check_probability_model (const svm_model *model)

Variables

const char * svm_type_table []
const char * kernel_type_table []

Define Documentation

#define INF   HUGE_VAL
 

#define Malloc type,
 )     (type *)malloc((n)*sizeof(type))
 

#define TAU   1e-12
 


Typedef Documentation

typedef float Qfloat
 

typedef signed char schar
 


Function Documentation

template<class S, class T>
void clone T *&  dst,
S *  src,
int  n
[inline]
 

void info const char *  fmt,
  ...
 

void info_flush  ) 
 

template<class T>
T max x,
y
[inline]
 

template<class T>
T min x,
y
[inline]
 

void multiclass_probability int  k,
double **  r,
double p
 

double powi double  base,
int  times
[inline]
 

double sigmoid_predict double  decision_value,
double  A,
double  B
 

void sigmoid_train int  l,
const double dec_values,
const double labels,
double A,
double B
 

void svm_binary_svc_probability const svm_problem prob,
const svm_parameter param,
double  Cp,
double  Cn,
double probA,
double probB
 

const char* svm_check_parameter const svm_problem prob,
const svm_parameter param
 

int svm_check_probability_model const svm_model model  ) 
 

void svm_cross_validation const svm_problem prob,
const svm_parameter param,
int  nr_fold,
double target
 

void svm_destroy_model svm_model model  ) 
 

void svm_destroy_param svm_parameter param  ) 
 

void svm_get_labels const svm_model model,
int *  label
 

int svm_get_nr_class const svm_model model  ) 
 

int svm_get_svm_type const svm_model model  ) 
 

double svm_get_svr_probability const svm_model model  ) 
 

void svm_group_classes const svm_problem prob,
int *  nr_class_ret,
int **  label_ret,
int **  start_ret,
int **  count_ret,
int *  perm
 

svm_model* svm_load_model const char *  model_file_name  ) 
 

double svm_predict const svm_model model,
const svm_node x
 

double svm_predict_probability const svm_model model,
const svm_node x,
double prob_estimates
 

void svm_predict_values const svm_model model,
const svm_node x,
double dec_values
 

int svm_save_model const char *  model_file_name,
const svm_model model
 

double svm_svr_probability const svm_problem prob,
const svm_parameter param
 

svm_model* svm_train const svm_problem prob,
const svm_parameter param
 

decision_function svm_train_one const svm_problem prob,
const svm_parameter param,
double  Cp,
double  Cn
 

template<class T>
void swap T &  x,
T &  y
[inline]
 


Variable Documentation

const char* kernel_type_table[]
 

Initial value:

{
        "linear","polynomial","rbf","sigmoid","precomputed",NULL
}

const char* svm_type_table[]
 

Initial value:

{
        "c_svc","nu_svc","one_class","epsilon_svr","nu_svr",NULL
}


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