ABSTRACT
It’s important to say at the outset that since classication is one of the most important and well-studied areas in machine learning, the number and diversity of classication methods is very large. ese range from things you’ve probably heard of like Neural Nets and naïve Bayes to obscure sounding things like AdaBoost with decision stumps. We won’t even begin to cover them all here. I will try to focus on a few methods that are easily connected to regression and clustering and that are widely used in molecular biology applications.
