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

Include dependency graph for svm.cpp:

Classes
class	Cache

struct	decision_function

struct	Cache::head_t

class	Kernel

class	ONE_CLASS_Q

class	QMatrix

struct	Solver::SolutionInfo

class	Solver

class	Solver_NU

class	SVC_Q

class	SVR_Q

Macros
#define	INF HUGE_VAL

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

#define	TAU 1e-12

Typedefs
typedef float	Qfloat

typedef signed char	schar

Functions
template<class S , class T >
static void	clone (T &dst, S src, int n)

static void	info (const char *fmt,...)

double	k_function (const svm_node x, const svm_node y, const svm_parameter &param)

template<class T >
static T	max (T x, T y)

template<class T >
static T	min (T x, T y)

static void	multiclass_probability (int k, double *r, double p)

static double	powi (double base, int times)

static void	print_string_stdout (const char *s)

static char *	readline (FILE *input)

static void	remove_zero_weight (svm_problem newprob, const svm_problem prob)

static double	sigmoid_predict (double decision_value, double A, double B)

static void	sigmoid_train (int l, const double dec_values, const double labels, double &A, double &B)

static void	solve_c_svc (const svm_problem prob, const svm_parameter param, double alpha, Solver::SolutionInfo si, double Cp, double Cn)

static void	solve_epsilon_svr (const svm_problem prob, const svm_parameter param, double alpha, Solver::SolutionInfo si)

static void	solve_nu_svc (const svm_problem prob, const svm_parameter param, double alpha, Solver::SolutionInfo si)

static void	solve_nu_svr (const svm_problem prob, const svm_parameter param, double alpha, Solver::SolutionInfo si)

static void	solve_one_class (const svm_problem prob, const svm_parameter param, double alpha, Solver::SolutionInfo si)

static 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_param (svm_parameter *param)

void	svm_free_and_destroy_model (svm_model **model_ptr_ptr)

void	svm_free_model_content (svm_model *model_ptr)

void	svm_get_labels (const svm_model model, int label)

int	svm_get_nr_class (const svm_model *model)

int	svm_get_nr_sv (const svm_model *model)

void	svm_get_sv_indices (const svm_model model, int indices)

int	svm_get_svm_type (const svm_model *model)

double	svm_get_svr_probability (const svm_model *model)

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

double	svm_hyper_w_normsqr_twoclass (const struct svm_model *model)

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)

double	svm_predict_values (const svm_model model, const svm_node x, double *dec_values)

double	svm_predict_values_twoclass (const struct svm_model model, const struct svm_node x)

int	svm_save_model (const char model_file_name, const svm_model model)

void	svm_set_print_string_function (void(print_func)(const char ))

static double	svm_svr_probability (const svm_problem prob, const svm_parameter param)

svm_model *	svm_train (const svm_problem prob, const svm_parameter param)

static decision_function	svm_train_one (const svm_problem prob, const svm_parameter param, double Cp, double Cn)

template<class T >
static void	swap (T &x, T &y)

Variables
static const char *	kernel_type_table []

int	libsvm_version = LIBSVM_VERSION

static char *	line = NULL

static int	max_line_len

static void(*	svm_print_string )(const char *) = &print_string_stdout

static const char *	svm_type_table []

Macro Definition Documentation

◆ INF

#define INF HUGE_VAL

Definition at line 71 of file svm.cpp.

◆ Malloc

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

Definition at line 73 of file svm.cpp.

◆ TAU

#define TAU 1e-12

Definition at line 72 of file svm.cpp.

Typedef Documentation

◆ Qfloat

typedef float Qfloat

Definition at line 46 of file svm.cpp.

◆ schar

typedef signed char schar

Definition at line 47 of file svm.cpp.

Function Documentation

◆ clone()

template<class S , class T >

static void clone	(	T *&	dst,
		S *	src,
		int	n
	)

inlinestatic

Definition at line 55 of file svm.cpp.

◆ info()

static void info	(	const char *	fmt,
			...
	)

static

Definition at line 92 of file svm.cpp.

◆ k_function()

double k_function	(	const svm_node *	x,
		const svm_node *	y,
		const svm_parameter &	param
	)

Definition at line 289 of file svm.cpp.

◆ max()

template<class T >

static T max	(	T	x,
		T	y
	)

inlinestatic

Definition at line 52 of file svm.cpp.

◆ min()

template<class T >

static T min	(	T	x,
		T	y
	)

inlinestatic

Definition at line 49 of file svm.cpp.

◆ multiclass_probability()

static void multiclass_probability	(	int	k,
		double **	r,
		double *	p
	)

static

Definition at line 1921 of file svm.cpp.

◆ powi()

static double powi	(	double	base,
		int	times
	)

inlinestatic

Definition at line 60 of file svm.cpp.

◆ print_string_stdout()

static void print_string_stdout ( const char * s )

static

Definition at line 75 of file svm.cpp.

◆ readline()

static char* readline ( FILE * input )

static

Definition at line 2905 of file svm.cpp.

◆ remove_zero_weight()

static void remove_zero_weight	(	svm_problem *	newprob,
		const svm_problem *	prob
	)

static

Definition at line 2170 of file svm.cpp.

◆ sigmoid_predict()

static double sigmoid_predict	(	double	decision_value,
		double	A,
		double	B
	)

static

Definition at line 1910 of file svm.cpp.

◆ sigmoid_train()

static void sigmoid_train	(	int	l,
		const double *	dec_values,
		const double *	labels,
		double &	A,
		double &	B
	)

static

Definition at line 1797 of file svm.cpp.

◆ solve_c_svc()

static void solve_c_svc	(	const svm_problem *	prob,
		const svm_parameter *	param,
		double *	alpha,
		Solver::SolutionInfo *	si,
		double	Cp,
		double	Cn
	)

static

Definition at line 1482 of file svm.cpp.

◆ solve_epsilon_svr()

static void solve_epsilon_svr	(	const svm_problem *	prob,
		const svm_parameter *	param,
		double *	alpha,
		Solver::SolutionInfo *	si
	)

static

Definition at line 1637 of file svm.cpp.

◆ solve_nu_svc()

static void solve_nu_svc	(	const svm_problem *	prob,
		const svm_parameter *	param,
		double *	alpha,
		Solver::SolutionInfo *	si
	)

static

Definition at line 1531 of file svm.cpp.

◆ solve_nu_svr()

static void solve_nu_svr	(	const svm_problem *	prob,
		const svm_parameter *	param,
		double *	alpha,
		Solver::SolutionInfo *	si
	)

static

Definition at line 1677 of file svm.cpp.

◆ solve_one_class()

static void solve_one_class	(	const svm_problem *	prob,
		const svm_parameter *	param,
		double *	alpha,
		Solver::SolutionInfo *	si
	)

static

Definition at line 1594 of file svm.cpp.

◆ svm_binary_svc_probability()

static void svm_binary_svc_probability	(	const svm_problem *	prob,
		const svm_parameter *	param,
		double	Cp,
		double	Cn,
		double &	probA,
		double &	probB
	)

static

Definition at line 1985 of file svm.cpp.

◆ svm_check_parameter()

const char* svm_check_parameter	(	const svm_problem *	prob,
		const svm_parameter *	param
	)

Definition at line 3186 of file svm.cpp.

◆ svm_check_probability_model()

int svm_check_probability_model ( const svm_model * model )

Definition at line 3307 of file svm.cpp.

◆ svm_cross_validation()

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

Definition at line 2461 of file svm.cpp.

◆ svm_destroy_param()

void svm_destroy_param ( svm_parameter * param )

Definition at line 3180 of file svm.cpp.

◆ svm_free_and_destroy_model()

void svm_free_and_destroy_model ( svm_model ** model_ptr_ptr )

Definition at line 3170 of file svm.cpp.

◆ svm_free_model_content()

void svm_free_model_content ( svm_model * model_ptr )

Definition at line 3138 of file svm.cpp.

◆ svm_get_labels()

void svm_get_labels	(	const svm_model *	model,
		int *	label
	)

Definition at line 2591 of file svm.cpp.

◆ svm_get_nr_class()

int svm_get_nr_class ( const svm_model * model )

Definition at line 2586 of file svm.cpp.

◆ svm_get_nr_sv()

int svm_get_nr_sv ( const svm_model * model )

Definition at line 2605 of file svm.cpp.

◆ svm_get_sv_indices()

void svm_get_sv_indices	(	const svm_model *	model,
		int *	indices
	)

Definition at line 2598 of file svm.cpp.

◆ svm_get_svm_type()

int svm_get_svm_type ( const svm_model * model )

Definition at line 2581 of file svm.cpp.

◆ svm_get_svr_probability()

double svm_get_svr_probability ( const svm_model * model )

Definition at line 2610 of file svm.cpp.

◆ svm_group_classes()

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

static

Definition at line 2110 of file svm.cpp.

◆ svm_hyper_w_normsqr_twoclass()

double svm_hyper_w_normsqr_twoclass ( const struct svm_model * model )

Definition at line 2622 of file svm.cpp.

◆ svm_load_model()

svm_model* svm_load_model ( const char * model_file_name )

Definition at line 2923 of file svm.cpp.

◆ svm_predict()

double svm_predict	(	const svm_model *	model,
		const svm_node *	x
	)

Definition at line 2744 of file svm.cpp.

◆ svm_predict_probability()

double svm_predict_probability	(	const svm_model *	model,
		const svm_node *	x,
		double *	prob_estimates
	)

Definition at line 2759 of file svm.cpp.

◆ svm_predict_values()

double svm_predict_values	(	const svm_model *	model,
		const svm_node *	x,
		double *	dec_values
	)

Definition at line 2668 of file svm.cpp.

◆ svm_predict_values_twoclass()

double svm_predict_values_twoclass	(	const struct svm_model *	model,
		const struct svm_node *	x
	)

Definition at line 2643 of file svm.cpp.

◆ svm_save_model()

int svm_save_model	(	const char *	model_file_name,
		const svm_model *	model
	)

Definition at line 2808 of file svm.cpp.

◆ svm_set_print_string_function()

void svm_set_print_string_function ( void(*)(const char *) print_func )

Definition at line 3315 of file svm.cpp.

◆ svm_svr_probability()

static double svm_svr_probability	(	const svm_problem *	prob,
		const svm_parameter *	param
	)

static

Definition at line 2076 of file svm.cpp.

◆ svm_train()

svm_model* svm_train	(	const svm_problem *	prob,
		const svm_parameter *	param
	)

Definition at line 2196 of file svm.cpp.

◆ svm_train_one()

static decision_function svm_train_one	(	const svm_problem *	prob,
		const svm_parameter *	param,
		double	Cp,
		double	Cn
	)

static

Definition at line 1732 of file svm.cpp.

◆ swap()

template<class T >

static void swap	(	T &	x,
		T &	y
	)

inlinestatic

Definition at line 54 of file svm.cpp.

Variable Documentation

◆ kernel_type_table

const char* kernel_type_table[]

static

Initial value:

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

Definition at line 2803 of file svm.cpp.

◆ libsvm_version

int libsvm_version = LIBSVM_VERSION

Definition at line 45 of file svm.cpp.

◆ line

char* line = NULL

static

Definition at line 2902 of file svm.cpp.

◆ max_line_len

int max_line_len

static

Definition at line 2903 of file svm.cpp.

◆ svm_print_string

void(* svm_print_string) (const char *) = &print_string_stdout

static

Definition at line 80 of file svm.cpp.

◆ svm_type_table

const char* svm_type_table[]

static

Initial value:

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

Definition at line 2798 of file svm.cpp.

Classes

Macros

Typedefs

Functions

Variables

Macro Definition Documentation

◆ INF

◆ Malloc

◆ TAU

Typedef Documentation

◆ Qfloat

◆ schar

Function Documentation

◆ clone()

◆ info()

◆ k_function()

◆ max()

◆ min()

◆ multiclass_probability()

◆ powi()

◆ print_string_stdout()

◆ readline()

◆ remove_zero_weight()

◆ sigmoid_predict()

◆ sigmoid_train()

◆ solve_c_svc()

◆ solve_epsilon_svr()

◆ solve_nu_svc()

◆ solve_nu_svr()

◆ solve_one_class()

◆ svm_binary_svc_probability()

◆ svm_check_parameter()

◆ svm_check_probability_model()

◆ svm_cross_validation()

◆ svm_destroy_param()

◆ svm_free_and_destroy_model()

◆ svm_free_model_content()

◆ svm_get_labels()

◆ svm_get_nr_class()

◆ svm_get_nr_sv()

◆ svm_get_sv_indices()

◆ svm_get_svm_type()

◆ svm_get_svr_probability()

◆ svm_group_classes()

◆ svm_hyper_w_normsqr_twoclass()

◆ svm_load_model()

◆ svm_predict()

◆ svm_predict_probability()

◆ svm_predict_values()

◆ svm_predict_values_twoclass()

◆ svm_save_model()

◆ svm_set_print_string_function()

◆ svm_svr_probability()

◆ svm_train()

◆ svm_train_one()

◆ swap()

Variable Documentation

◆ kernel_type_table

◆ libsvm_version

◆ line

◆ max_line_len

◆ svm_print_string

◆ svm_type_table