LibSVM

Package

weka.classifiers.functions

Synopsis

A wrapper class for the libsvm tools (the libsvm classes, typically the jar file, need to be in the classpath to use this classifier).
LibSVM runs faster than SMO since it uses LibSVM to build the SVM classifier.
LibSVM allows users to experiment with One-class SVM, Regressing SVM, and nu-SVM supported by LibSVM tool. LibSVM reports many useful statistics about LibSVM classifier (e.g., confusion matrix,precision, recall, ROC score, etc.).

Yasser EL-Manzalawy (2005). WLSVM. URL http://www.cs.iastate.edu/~yasser/wlsvm/.

Chih-Chung Chang, Chih-Jen Lin (2001). LIBSVM - A Library for Support Vector Machines. URL http://www.csie.ntu.edu.tw/~cjlin/libsvm/.

Available in Weka 3.6.x - 3.7.1. Available via the package management system for Weka >= 3.7.2 (LibSVM).

Options

The table below describes the options available for LibSVM.

Option	Description
SVMType	The type of SVM to use.
cacheSize	The cache size in MB.
coef0	The coefficient to use.
cost	The cost parameter C for C-SVC, epsilon-SVR and nu-SVR.
debug	If set to true, classifier may output additional info to the console.
degree	The degree of the kernel.
eps	The tolerance of the termination criterion.
gamma	The gamma to use, if 0 then 1/max_index is used.
kernelType	The type of kernel to use
loss	The epsilon for the loss function in epsilon-SVR.
normalize	Whether to normalize the data.
nu	The value of nu for nu-SVC, one-class SVM and nu-SVR.
probabilityEstimates	Whether to generate probability estimates instead of -1/+1 for classification problems.
shrinking	Whether to use the shrinking heuristic.
weights	The weights to use for the classes, if empty 1 is used by default.

Capabilities

The table below describes the capabilites of LibSVM.

Capability	Supported
Class	Nominal class, Missing class values, Binary class
Attributes	Empty nominal attributes, Numeric attributes, Unary attributes, Binary attributes, Date attributes, Nominal attributes
Min # of instances	1