I have been using multiple kernel learning (MKL) to train a classifier and got some exposure to the field. However, I am quite new to machine learning and I have only an intuitive understanding of the subject. I have recently been told that the MKL algorithm I am using might not be the best choice for what I am trying to do, which leads to my question:
How do you go about choosing the best algorithm for the job - say for example SimpleMKL, AverageMKL or EasyMKL? What is the intuition in the difference between these and what is the "ideal" application for each?