C# Class Encog.MathUtil.LIBSVM.svm

Afficher le fichier Open project: encog/encog-silverlight-core

Méthodes publiques

Méthode Description
svm_check_parameter ( svm_problem prob, svm_parameter param ) : String
svm_check_probability_model ( svm_model model ) : int
svm_cross_validation ( svm_problem prob, svm_parameter param, int nr_fold, double target ) : void
svm_get_labels ( svm_model model, int label ) : void
svm_get_nr_class ( svm_model model ) : int
svm_get_svm_type ( svm_model model ) : int
svm_get_svr_probability ( svm_model model ) : double
svm_load_model ( StringReader fp ) : svm_model
svm_predict ( svm_model model, svm_node x ) : double
svm_predict_probability ( svm_model model, svm_node x, double prob_estimates ) : double
svm_predict_values ( svm_model model, svm_node x, double dec_values ) : void
svm_save_model ( StreamWriter fp, svm_model model ) : void
svm_train ( svm_problem prob, svm_parameter param ) : svm_model

Private Methods

Méthode Description
atof ( String s ) : double
atoi ( String s ) : int
multiclass_probability ( int k, double r, double p ) : void
sigmoid_predict ( double decision_value, double A, double B ) : double
sigmoid_train ( int l, double dec_values, double labels, double probAB ) : void
solve_c_svc ( svm_problem prob, svm_parameter param, double alpha, Solver si, double Cp, double Cn ) : void
solve_epsilon_svr ( svm_problem prob, svm_parameter param, double alpha, Solver si ) : void
solve_nu_svc ( svm_problem prob, svm_parameter param, double alpha, Solver si ) : void
solve_nu_svr ( svm_problem prob, svm_parameter param, double alpha, Solver si ) : void
solve_one_class ( svm_problem prob, svm_parameter param, double alpha, Solver si ) : void
svm_binary_svc_probability ( svm_problem prob, svm_parameter param, double Cp, double Cn, double probAB ) : void
svm_svr_probability ( svm_problem prob, svm_parameter param ) : double
svm_train_one ( svm_problem prob, svm_parameter param, double Cp, double Cn ) : decision_function

Method Details

svm_check_parameter() public static méthode

public static svm_check_parameter ( svm_problem prob, svm_parameter param ) : String
prob svm_problem
param svm_parameter
Résultat String

svm_check_probability_model() public static méthode

public static svm_check_probability_model ( svm_model model ) : int
model svm_model
Résultat int

svm_cross_validation() public static méthode

public static svm_cross_validation ( svm_problem prob, svm_parameter param, int nr_fold, double target ) : void
prob svm_problem
param svm_parameter
nr_fold int
target double
Résultat void

svm_get_labels() public static méthode

public static svm_get_labels ( svm_model model, int label ) : void
model svm_model
label int
Résultat void

svm_get_nr_class() public static méthode

public static svm_get_nr_class ( svm_model model ) : int
model svm_model
Résultat int

svm_get_svm_type() public static méthode

public static svm_get_svm_type ( svm_model model ) : int
model svm_model
Résultat int

svm_get_svr_probability() public static méthode

public static svm_get_svr_probability ( svm_model model ) : double
model svm_model
Résultat double

svm_load_model() public static méthode

public static svm_load_model ( StringReader fp ) : svm_model
fp System.IO.StringReader
Résultat svm_model

svm_predict() public static méthode

public static svm_predict ( svm_model model, svm_node x ) : double
model svm_model
x svm_node
Résultat double

svm_predict_probability() public static méthode

public static svm_predict_probability ( svm_model model, svm_node x, double prob_estimates ) : double
model svm_model
x svm_node
prob_estimates double
Résultat double

svm_predict_values() public static méthode

public static svm_predict_values ( svm_model model, svm_node x, double dec_values ) : void
model svm_model
x svm_node
dec_values double
Résultat void

svm_save_model() public static méthode

public static svm_save_model ( StreamWriter fp, svm_model model ) : void
fp System.IO.StreamWriter
model svm_model
Résultat void

svm_train() public static méthode

public static svm_train ( svm_problem prob, svm_parameter param ) : svm_model
prob svm_problem
param svm_parameter
Résultat svm_model