Uses of Class de.bwaldvogel.liblinear.Problem

Uses of Problem in de.bwaldvogel.liblinear

Fields in de.bwaldvogel.liblinear declared as Problem
Modifier and Type	Field	Description
`(package private) Problem`	L2R_ErmFunction.`prob`
`private Problem`	SolverMCSVM_CS.`prob`
`private Problem`	Train.`prob`

Methods in de.bwaldvogel.liblinear that return Problem
Modifier and Type	Method	Description
`private static Problem`	Train.`constructProblem(java.util.List<java.lang.Double> vy, java.util.List<Feature[]> vx, int max_index, double bias)`
`Problem`	Train.`getProblem()`
`static Problem`	Problem.`readFromFile(java.io.File file, double bias)`	Deprecated. use `readFromFile(Path, double)` instead
`static Problem`	Problem.`readFromFile(java.io.File file, java.nio.charset.Charset charset, double bias)`	Deprecated. use `readFromFile(Path, Charset, double)` instead
`static Problem`	Problem.`readFromFile(java.nio.file.Path path, double bias)`	see `Train.readProblem(Path, double)`
`static Problem`	Problem.`readFromFile(java.nio.file.Path path, java.nio.charset.Charset charset, double bias)`	see `Train.readProblem(Path, Charset, double)`
`static Problem`	Problem.`readFromStream(java.io.InputStream inputStream, double bias)`	see `Train.readProblem(InputStream, double)`
`static Problem`	Problem.`readFromStream(java.io.InputStream inputStream, java.nio.charset.Charset charset, double bias)`	see `Train.readProblem(InputStream, Charset, double)`
`static Problem`	Train.`readProblem(java.io.File file, double bias)`	Deprecated. use `Train.readProblem(Path, double)` instead
`static Problem`	Train.`readProblem(java.io.File file, java.nio.charset.Charset charset, double bias)`	Deprecated. use `Train.readProblem(Path, Charset, double)` instead
`static Problem`	Train.`readProblem(java.io.InputStream inputStream, double bias)`
`static Problem`	Train.`readProblem(java.io.InputStream inputStream, java.nio.charset.Charset charset, double bias)`
`static Problem`	Train.`readProblem(java.nio.file.Path path, double bias)`	reads a problem from LibSVM format
`static Problem`	Train.`readProblem(java.nio.file.Path path, java.nio.charset.Charset charset, double bias)`
`(package private) static Problem`	Linear.`transpose(Problem prob)`

Methods in de.bwaldvogel.liblinear with parameters of type Problem
Modifier and Type	Method	Description
`private static double`	Linear.`calc_max_p(Problem prob)`
`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 Linear.GroupClassesReturn`	Linear.`groupClasses(Problem prob, int[] perm)`
`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)`
`(package private) static Problem`	Linear.`transpose(Problem prob)`

Constructors in de.bwaldvogel.liblinear with parameters of type Problem
Constructor	Description
`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)`
`L2R_LrFunction(Problem prob, Parameter param, double[] C)`
`SolverMCSVM_CS(Problem prob, int nr_class, double[] C, double eps, java.util.Random random)`