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<br>
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=== <br> 1. Motivation  ===
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*Most likely converge as number of number of training sample increase.
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*Simpler than alternate methods such as Bayesian technique.
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=== <br> 2. Motivation  ===
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*Statistical Density Theory Context
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**Given c classes + some knowledge about features $x \in \mathbb{R}^n$ (or some other space)
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[[Image:Zhenpeng_Selecture_1.png]]
 
[[Image:Zhenpeng_Selecture_1.png]]

Revision as of 20:58, 5 May 2014


Expected Value of MLE estimate over standard deviation and expected deviation

A slecture by ECE student Zhenpeng Zhao

Partly based on the ECE662 Spring 2014 lecture material of Prof. Mireille Boutin.




1. Motivation

  • Most likely converge as number of number of training sample increase.
  • Simpler than alternate methods such as Bayesian technique.



2. Motivation

  • Statistical Density Theory Context
    • Given c classes + some knowledge about features $x \in \mathbb{R}^n$ (or some other space)


Zhenpeng Selecture 1.png Zhenpeng Selecture 2.png Zhenpeng Selecture 3.png Zhenpeng Selecture 4.png Zhenpeng Selecture 5.png



(create a question page and put a link below)

Questions and comments

If you have any questions, comments, etc. please post them on https://kiwi.ecn.purdue.edu/rhea/index.php/ECE662Selecture_ZHenpengMLE_Ques.


Back to ECE662, Spring 2014

Alumni Liaison

has a message for current ECE438 students.

Sean Hu, ECE PhD 2009