Bayesian Parameter Estimation

Abstract

Prior to learning the content in this media, students have learned how to design a classifier if they already know the prior probabilities, p omega, and a class conditional density, p of x given omega. In geneneral, students do not know these parameters. They must be estimated using sample data. In this media, students learn how to estimate them. This media examines two standard techniques for estimating these paramters: maximun likelihood estimation and bayasian paramter estimation.