Uses of Class
pt.tumba.ngram.svm.SVMParameter

Packages that use SVMParameter
pt.tumba.ngram.svm Implementation of Support Vector Machines classification and regression that can be used to categorize text files using N-Grams as features. 
 

Uses of SVMParameter in pt.tumba.ngram.svm
 

Fields in pt.tumba.ngram.svm declared as SVMParameter
protected  SVMParameter SVMCategorizer.param
           
(package private)  SVMParameter SVMModel.params
          The parameters of this model.
 

Methods in pt.tumba.ngram.svm with parameters of type SVMParameter
(package private) static double Kernel.kernelFunction(SVMNode[] x, SVMNode[] y, SVMParameter param)
          Returns the value of a single kernel evaluation.
private static void SVM.solveCSVC(SVMProblem prob, SVMParameter param, double[] alpha, Solver.SolutionInfo si, double Cp, double Cn)
          Solve the C-Support Vector classification problem.
private static void SVM.solveEpsilonSVR(SVMProblem prob, SVMParameter param, double[] alpha, Solver.SolutionInfo si)
          Solve the Epsilon-Support Vector Regression Problem
private static void SVM.solveNUSVC(SVMProblem prob, SVMParameter param, double[] alpha, Solver.SolutionInfo si)
          Solve the Nu-Support Vector Classification problem.
private static void SVM.solveNUSVR(SVMProblem prob, SVMParameter param, double[] alpha, Solver.SolutionInfo si)
          Solve the Nu-Support Vector Regression Problem
private static void SVM.solveOneClass(SVMProblem prob, SVMParameter param, double[] alpha, Solver.SolutionInfo si)
          Solve the SVM Distribution Estimation Problem.
private static void SVM.svmBinarySVCProbability(SVMProblem prob, SVMParameter param, double Cp, double Cn, double[] probAB)
          Cross-validation decision values for probability estimates.
static java.lang.String SVM.svmCheckParameter(SVMProblem prob, SVMParameter param)
          Check the parameters given to an SVM problem.
static void SVM.svmCrossValidation(SVMProblem prob, SVMParameter param, int nr_fold, double[] target)
          Perform cross validation
private static double SVM.svmSVRProbability(SVMProblem prob, SVMParameter param)
          Return parameter of a Laplace distribution
static SVMModel SVM.svmTrain(SVMProblem prob, SVMParameter param)
          Train the SVM.
(package private) static SVM.decisionFunction SVM.svmTrainOne(SVMProblem prob, SVMParameter param, double Cp, double Cn)
          Computation for one step of the training procedure.
 

Constructors in pt.tumba.ngram.svm with parameters of type SVMParameter
Kernel(int l, SVMNode[][] x_, SVMParameter param)
          Kernel constructor, prepares to calculate the l*l kernel matrix.
ONECLASSQ(SVMProblem prob, SVMParameter param)
           
SVCQ(SVMProblem prob, SVMParameter param, byte[] y_)
           
SVRQ(SVMProblem prob, SVMParameter param)