Recommendations on which algorithms in WEKA perform well at classifier/clustering underrepresented classes in large data sets.

Hello /r/machinelearning,

If anyone has already been the through the gauntlet of working with data sets with underrepresented classes I'd be grateful for any recommendation on which algorithms and parameters you prefer.

I have a data set with about 10,000 samples and only 14 of a certain class. So far, decision table, and SMO have been doing poorly at classifying the underrepresented class during the training phase. I'll keep running it through the different classifiers.

Thanks in advance!