The Expectation Maximization Algorithm

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Issue:

Science

 

Written by:

Beth E

 

Date added:

August 29, 2015

 

Level:

University

 

Grade:

A

 

No of pages / words:

2 / 410

 

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6188 times

 

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Essay content:

It includes a graphical example to provide some intuition. 1 Intuitive Explanation of EM EM is an iterative optimization method to estimate some unknown parameters, given measurement data U. However, we are not given some “hidden” nuisance variables J, which need to be integrated out. In particular, we want to maximize the posterior probability of the parameters  given the data U, marginalizing over J:  = argmax  X J2Jn P(; JjU) (1) The intuition behind EM is an old one: alternate between estimating the unknowns  and the hidden variables J...
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In particular, we want to maximize the posterior probability of the parameters  given the data U, marginalizing over J:  = argmax  X J2Jn P(; JjU) (1) The intuition behind EM is an old one: alternate between estimating the unknowns  and the hidden variables J. This idea has been around for a long time...
displayed 300 characters

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