> Yeah, that is pretty much the entire objective of SVMs.
Which is hard to do by hand in many dimensions but almost trivial in 2. I haven't read the paper but maybe the OP is complaining about something like that?
Yes, the data is essentially 1-dimensional and looks like "CCC MMMMMMMM". (Seriously, look at Figure 2 graph H in the paper.) It seems entirely gratuitous to use machine learning to build a SVM classifier to separate the C's from the M's, when it's obvious that the C's are on the left and the M's on the right.
Which is hard to do by hand in many dimensions but almost trivial in 2. I haven't read the paper but maybe the OP is complaining about something like that?