I am unable to clearly see the main differences between SVM & SMO. While I get the fact that SMO provides better algorithm for QP solvers but I see that when I use this in Weka on my MacBook it nearly took 12 hours for 46 features (≈40K feature vectors) of size 5MB dataset (whereas SVM took about 50 minutes).
Where does the optimization kick in? or Whats the catch. FYI, I am trying to build a binary classifier.