Uses of Class
de.bwaldvogel.liblinear.Parameter

Uses of Parameter in de.bwaldvogel.liblinear

Fields in de.bwaldvogel.liblinear declared as Parameter

Modifier and Type	Field	Description
private Parameter	Train.param

Methods in de.bwaldvogel.liblinear that return Parameter

Modifier and Type	Method	Description
Parameter	Parameter.clone()
Parameter	Train.getParameter()

Methods in de.bwaldvogel.liblinear with parameters of type Parameter

Modifier and Type	Method	Description
private static double	Linear.calc_start_C(Problem prob, Parameter param)
static void	Linear.crossValidation(Problem prob, Parameter param, int nr_fold, double[] target)
static ParameterCSearchResult	Linear.find_parameter_C(Problem prob, Parameter param_tmp, double start_C, double max_C, int[] fold_start, int[] perm, Problem[] subprob, int nr_fold)
static ParameterSearchResult	Linear.findParameters(Problem prob, Parameter param, int nr_fold, double start_C, double start_p)
private static int	Linear.solve_l1r_l2_svc(Problem prob_col, Parameter param, double[] w, double Cp, double Cn, double eps, int max_iter)	A coordinate descent algorithm for L1-regularized L2-loss support vector classification
private static int	Linear.solve_l1r_lr(Problem prob_col, Parameter param, double[] w, double Cp, double Cn, double eps, int max_iter)	A coordinate descent algorithm for L1-regularized logistic regression problems
private static int	Linear.solve_l2r_l1l2_svc(Problem prob, Parameter param, double[] w, double Cp, double Cn, int max_iter)	A coordinate descent algorithm for L1-loss and L2-loss SVM dual problems
private static int	Linear.solve_l2r_l1l2_svr(Problem prob, Parameter param, double[] w, int max_iter)	A coordinate descent algorithm for L1-loss and L2-loss epsilon-SVR dual problem min_\beta 0.5\beta^T (Q + diag(lambda)) \beta - p \sum_{i=1}^l|\beta_i| + \sum_{i=1}^l yi\beta_i, s.t.
private static int	Linear.solve_l2r_lr_dual(Problem prob, Parameter param, double[] w, double Cp, double Cn, int max_iter)	A coordinate descent algorithm for the dual of L2-regularized logistic regression problems
(package private) static int	Linear.solve_oneclass_svm(Problem prob, Parameter param, double[] w, MutableDouble rho, int max_iter)
static Model	Linear.train(Problem prob, Parameter param)
private static void	Linear.train_one(Problem prob, Parameter param, double[] w, double Cp, double Cn)

Constructors in de.bwaldvogel.liblinear with parameters of type Parameter

Modifier	Constructor	Description
(package private)	L2R_ErmFunction(Problem prob, Parameter parameter, double[] C)
	L2R_L2_SvcFunction(Problem prob, Parameter param, double[] C)
	L2R_L2_SvrFunction(Problem prob, Parameter param, double[] C)
(package private)	L2R_LrFunction(Problem prob, Parameter param, double[] C)