I'm trying to classify short reads to a number of bins (usually no more than 5). After looking for a while in the libSVM faq as well as in relevant papers, I think that one-class SVM classifiers may be what I'm looking for; I just need to know whether a read belongs to a bin or not. This is what a one-class classifier will tell me, right?
The problem is that after preparing the training set (have tried 500 and 1000 vectors) and doing the testing, classification accuracy can't get above 32% (lots of false negatives).
I noticed that there's a one-class-specific parameter, named "nu" (-n switch in svm-train). I wrote a Perl script and tried different values for it (from 0.001 to 1 in 0.001 steps) but can't get a decent accuracy...
Has anyone more experience with such classifiers and give me some hints, please?