Bayesian Parameter Estimation
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Authors
Subjects
maximum likelihood
bayesian parameter estimation
sample data
estimate parameters
bayesian parameter estimation
sample data
estimate parameters
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Date of Issue
2006-12-11
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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.
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Interactive Media Element (IME)
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present
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Interactive Media Element
Presentation
Interactive Media Element
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This publication is a work of the U.S. Government as defined in Title 17, United States Code, Section 101. Copyright protection is not available for this work in the United States.