Multiclass Classification - mit.edu

Multiclass Classification Class 06, 25 Feb 2008. Ryan Rifkin It is a tale Told by an idiot, full of sound and fury, Signifying nothing.. Macbeth, Act V, Scene V. What Is Multiclass Classification? Each training point belongs to one of N different classes. The goal is to construct a function which, given a new data point, will correctly predict the class to which the new point belongs. What Isn't Multiclass Classification? There are many scenarios in which there are multiple cate- gories to which points belong, but a given point can belong to multiple categories. In its most basic form, this problem decomposes trivially into a set of unlinked binary problems, which can be solved naturally using our techniques for bi- nary classification. A First Idea Suppose we knew the density, pi(x), for each of the N. classes. Then, we would predict using f (x) = arg max pi(x). i 1,..,N. Of course we don't know the densities, but we could esti- mate them using classical techniques. The Problem With Densities, and Motivation Estimating densities is hard, especially in high dimensions with limited data.

What Isn’t Multiclass Classification? There are many scenarios in which there are multiple cate-gories to which points belong, but a given point can belong

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