Java weka.classifiers.functions LibSVM fields, constructors, methods, implement or subclass

Example usage for Java weka.classifiers.functions LibSVM fields, constructors, methods, implement or subclass

Introduction

In this page you can find the methods, fields and constructors for weka.classifiers.functions LibSVM.

The text is from its open source code.

Field

int	SVMTYPE_C_SVC SVM type C-SVC (classification).
int	SVMTYPE_NU_SVC SVM type nu-SVC (classification).
int	SVMTYPE_ONE_CLASS_SVM SVM type one-class SVM (classification).
int	SVMTYPE_EPSILON_SVR SVM type epsilon-SVR (regression).
int	SVMTYPE_NU_SVR SVM type nu-SVR (regression).
Tag[]	TAGS_SVMTYPE SVM types.
int	KERNELTYPE_LINEAR kernel type linear: u'*v.
int	KERNELTYPE_POLYNOMIAL kernel type polynomial: (gammau'v + coef0)^degree.
int	KERNELTYPE_RBF kernel type radial basis function: exp(-gamma*\|u-v\|^2).
int	KERNELTYPE_SIGMOID kernel type sigmoid: tanh(gammau'v + coef0).
Tag[]	TAGS_KERNELTYPE the different kernel types.

Constructor

	LibSVM

Method

void	buildClassifier(Instances insts) builds the classifier.
void	setCacheSize(double value) Sets cache memory size in MB (default 40).
void	setCoef0(double value) Sets coef (default 0).
void	setCost(double value) Sets the parameter C of C-SVC, epsilon-SVR, and nu-SVR (default 1).
void	setDegree(int value) Sets the degree of the kernel.
void	setEps(double value) Sets tolerance of termination criterion (default 0.001).
void	setGamma(double value) Sets gamma (default = 1/no of attributes).
void	setKernelType(SelectedTag value) Sets type of kernel function (default KERNELTYPE_RBF).
void	setLoss(double value) Sets the epsilon in loss function of epsilon-SVR (default 0.1).
void	setNormalize(boolean value) whether to normalize input data.
void	setNu(double value) Sets nu of nu-SVC, one-class SVM, and nu-SVR (default 0.5).
void	setOptions(String[] options) Sets the classifier options Valid options are: -S <int> Set type of SVM (default: 0) 0 = C-SVC 1 = nu-SVC 2 = one-class SVM 3 = epsilon-SVR 4 = nu-SVR -K <int> Set type of kernel function (default: 2) 0 = linear: u'v 1 = polynomial: (gammau'v + coef0)^degree 2 = radial basis function: exp(-gamma\|u-v\|^2) 3 = sigmoid: tanh(gammau'v + coef0) -D <int> Set degree in kernel function (default: 3) -G <double> Set gamma in kernel function (default: 1/k) -R <double> Set coef0 in kernel function (default: 0) -C <double> Set the parameter C of C-SVC, epsilon-SVR, and nu-SVR (default: 1) -N <double> Set the parameter nu of nu-SVC, one-class SVM, and nu-SVR (default: 0.5) -Z Turns on normalization of input data (default: off) -J Turn off nominal to binary conversion.
void	setShrinking(boolean value) whether to use the shrinking heuristics.
void	setSVMType(SelectedTag value) Sets type of SVM (default SVMTYPE_C_SVC).