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Weka LibSVM (WLSVM): Integrating LibSVM into Weka Environment


Weka and LibSVM are two efficient software tools for building SVM classifiers. Each one of these two tools has its points of strength and weakness. Weka has a GUI and produces many useful statistics (e.g. confusion matrix, precision, recall, F-measure, and ROC scores). LibSVM runs much faster than Weka SMO and supports several SVM methods (e.g. One-class SVM, nu-SVM, and R-SVM). Weka LibSVM (WLSVM) combines the merits of the two tools. WLSVM can be viewed as an implementation of the LibSVM running under Weka environment.

How To Use

  • Download and unzip the file
  • Add the jars libsvm.jar and wlsvm.jar to your java project
  • Use WLSVM as any other weka classifier
Notes: Your java project should also have weka.jar.

WLSVM Options

-S  set type of SVM (default 0)	 
		 0 = C-SVC
		 1 = nu-SVC
		 2 = one-class SVM
		 3 = epsilon-SVR
		 4 = nu-SVR
-K  set type of kernel function (default 2)	 
		 0 = linear: u'*v
		 1 = polynomial: (gamma*u'*v + coef0)^degree
		 2 = radial basis function: exp(-gamma*|u-v|^2)
		 3 = sigmoid: tanh(gamma*u'*v + coef0)
-D  set degree in kernel function (default 3)	 
-G  set gamma in kernel function (default 1/k)	 
-R  set coef0 in kernel function (default 0)	 
-C  set the parameter C of C-SVC, epsilon-SVR, and nu-SVR (default 1)	 
-N  set the parameter nu of nu-SVC, one-class SVM, and nu-SVR (default 0.5)
-Z  whether to normalize input data, 0 or 1 (default 0)
-P  set the epsilon in loss function of epsilon-SVR (default 0.1)
-M  set cache memory size in MB (default 40)
-E  set tolerance of termination criterion (default 0.001)
-H  whether to use the shrinking heuristics, 0 or 1 (default 1)
-W  set the parameters C of class i to weight[i]*C, for C-SVC (default 1)


If you would like to cite WLSVM, cite the following URL:
Yasser EL-Manzalawy and Vasant Honavar, WLSVM : Integrating LibSVM into Weka Environment, 2005. Software available at

The bibtex format is as follows
  author =	 {Yasser EL-Manzalawy and Vasant Honavar},
  title =	 {{WLSVM}: Integrating LibSVM into Weka Environment},
  year =	 {2005},
  note =	 {Software available at \url{}}


If you have any problems using WLSVM or if you have any suggestions. Please contact Yasser EL-Manzalawy