howto-svmlight-weka

wekaUT是 university texas austin 开发的基于weka的半指导学习(semi supervised learning)的分类器

1)  Create a 'sparse' directory in weka/classifiers and put SVMlight.java there.

2)  Look at the directories for SVMlight binaries and temporary files which are 
defined on lines 65 and 67 in SVMlight.java.  Change these to appropriate 
directories in your local filesystem. 

3)  Compile SVMlight.java (javac SVMlight.java).  Make sure you have ./, ../, and 
../.. in your CLASSPATH (or compile using "javac -classpath "./;../;../..;../../..").
If you are using Weka 3.4 or later, make Classifier the parent class instead of 
DistributionClassifier. 

4) Put svm_classify_std.c into the SVMlight directory; replace all occurrences of
svm_classify with svm_classify_std in SVMlight's Makefile, and compile the 
svm_classify_std binary by running make (the only difference between the two is 
output that is a bit easier to parse from Java). 

5)  If you are using the Weka Experimenter GUI, add weka.classifiers.sparse.SVMlight 
as one of Classifier's and DistributionClassifier's in 
weka/gui/GenericObjectEditor.props (just Classifier's for Weka 3.4 and later).