Transcription of Lecture10: Expectation-Maximization Algorithm
{{id}} {{{paragraph}}}
Example: barber
Lecture10: Expectation-Maximization Algorithm
ECE 645: Estimation TheorySpring 2015 Instructor: Prof. Stanley H. ChanLecture 10: Expectation-Maximization Algorithm (LaTeX prepared by Shaobo Fang)May 4, 2015 This lecture note is based on ECE 645 (Spring 2015) by Prof. StanleyH. Chan in the School of Electricaland Computer Engineering at Purdue MotivationConsider a set of data points with their classes labeled, and assume that each class is a Gaussian as shownin Figure 1(a). Given this set of data points, finding the means of twoGaussian can be done easily byestimating the sample mean, as the class labels are imagine that the classes are not labeled as shown in Figure 1(b).
Lecture10: Expectation-Maximization Algorithm (LaTeXpreparedbyShaoboFang) May4,2015 This lecture note is based on ECE 645 (Spring 2015) by Prof. Stanley H. Chan in the School of Electrical and Computer Engineering at Purdue University. 1 Motivation Consider a set of data points with their classes labeled, and assume that each class is a ...
Loading..
Tags:
Information
Domain:
Source:
Link to this page:
Please notify us if you found a problem with this document: