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| − | *[[ | + | *Please take the time to write your advice for future students on the [[Peer_Legacy_ECE662|"ECE662 Peer Legacy" page]]. You can read the [[Peer_Legacy_ECE301|ECE301 peer legacy page]] to see some examples. |
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| + | == References== | ||
| + | *[http://www.google.com/url?sa=t&rct=j&q=&esrc=s&source=web&cd=2&ved=0CDgQFjAB&url=http%3A%2F%2Fresearch.microsoft.com%2Fpubs%2F67119%2Fsvmtutorial.pdf&ei=RiiHT_jmBOrL0QHlvo3bBw&usg=AFQjCNFaFZdMSTqar2SsbbHMxOC3oXuaYQ&sig2=sXtX5ecwEdHxoViGqEcGYA A tutorial on support vector machines for pattern recognition] | ||
== Relevant Material == | == Relevant Material == | ||
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== Lecture Blog == | == Lecture Blog == | ||
| − | [[Lecture1ECE662S12|Lecture 1]], [[Lecture2ECE662S12|2]], [[Lecture3ECE662S12|3]] ,[[Lecture4ECE662S12|4]], [[Lecture5ECE662S12|5]], [[Lecture6ECE662S12|6]], [[Lecture7ECE662S12|7]], [[Lecture8ECE662S12|8]], [[Lecture9ECE662S12|9]] | + | [[Lecture1ECE662S12|Lecture 1]], [[Lecture2ECE662S12|2]], [[Lecture3ECE662S12|3]] ,[[Lecture4ECE662S12|4]], [[Lecture5ECE662S12|5]], [[Lecture6ECE662S12|6]], [[Lecture7ECE662S12|7]], [[Lecture8ECE662S12|8]], [[Lecture9ECE662S12|9]], [[Lecture10ECE662S12|10]], [[Lecture11ECE662S12|11]], [[Lecture12ECE662S12|12]], [[Lecture13ECE662S12|13]], [[Lecture14ECE662S12|14]], [[Lecture15ECE662S12|15]], [[Lecture16ECE662S12|16]], [[Lecture17ECE662S12|17]], [[Lecture18ECE662S12|18]], [[Lecture19ECE662S12|19]], [[Lecture20ECE662S12|20]], [[Lecture21ECE662S12|21]], [[Lecture22ECE662S12|22]], [[Lecture23ECE662S12|23]], [[Lecture24ECE662S12|24]], [[Lecture25ECE662S12|25]], [[Lecture26ECE662S12|26]], [[Lecture27ECE662S12|27]], [[Lecture28ECE662S12|28]], [[Lecture29ECE662S12|29]], [[Lecture30ECE662S12|30]] |
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*[[Hw1 ECE662 S12|first homework]], due Tuesday February 14, 11:59pm. [[Hw1 discussion ECE662 S12|HW1 discussion]] | *[[Hw1 ECE662 S12|first homework]], due Tuesday February 14, 11:59pm. [[Hw1 discussion ECE662 S12|HW1 discussion]] | ||
| − | + | *[[HW1_peer_review_ECE662S12|Peer review of homework 1]], due Thursday February 23, 11:59pm. | |
| + | *[[Hw2 ECE662 S12|second homework]], due Thursday April 5, 11:59pm. [[Hw2 discussion ECE662 S12|HW2 discussion]] | ||
| + | *[[HW2_peer_review_ECE662S12|Peer review of homework 2]], due Tuesday April 17, 11:59pm. | ||
| + | *[[Hw3_ECE662_S12|Third (and last) homework]], test data classification due 11:59pm, Friday April 27; report due 11:59pm, Monday April 30. [[Hw3 discussion ECE662 S12|HW3 discussion]] | ||
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| + | ==[[Hw3_ECE662_S12|Pattern Recognition Contest]]== | ||
| + | Our [[Hw3_ECE662_S12|third and last homework]] this semester is a pattern recognition contest using real-world data kindly provided by one of our industrial partners. | ||
| + | *Results of the contest | ||
| + | *Discussion of result by Prof. Boutin | ||
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Latest revision as of 07:20, 25 June 2012
Contents
ECE662: "Pattern Recognition and Decision Making Processes", Spring 2012
Note: CS662 is a cross-listing of ECE 662. In other words, they are the same exact course.
Message area:
- Please take the time to write your advice for future students on the "ECE662 Peer Legacy" page. You can read the ECE301 peer legacy page to see some examples.
Course information
Instructor: Prof. Boutin
Office: MSEE342
Office hours: listed here
Lecture: TuTh 10:30-11:45 in PHYS 223
References
Relevant Material
- Pattern Recognition Glossary (written by ECE662 students in 2010)
- Examples of recognition problems as CAPCHAS
- "What is pattern recognition?" (class notes from 2010, written by students)
- Page discussing difference between choosing most likely outcome always, or randomly guessing following the relative probabilities of the outcome
- The effect of adding correlated features
- A student page about the effect of severe class imabalance
- UCI Data Set: Data sorted according to categories(Life Sciences, Physical Sciences etc.)
Lecture Blog
Lecture 1, 2, 3 ,4, 5, 6, 7, 8, 9, 10, 11, 12, 13, 14, 15, 16, 17, 18, 19, 20, 21, 22, 23, 24, 25, 26, 27, 28, 29, 30
Homework
- first homework, due Tuesday February 14, 11:59pm. HW1 discussion
- Peer review of homework 1, due Thursday February 23, 11:59pm.
- second homework, due Thursday April 5, 11:59pm. HW2 discussion
- Peer review of homework 2, due Tuesday April 17, 11:59pm.
- Third (and last) homework, test data classification due 11:59pm, Friday April 27; report due 11:59pm, Monday April 30. HW3 discussion
Pattern Recognition Contest
Our third and last homework this semester is a pattern recognition contest using real-world data kindly provided by one of our industrial partners.
- Results of the contest
- Discussion of result by Prof. Boutin
