Download Monday March 29, 2004

Monday March 29, 2004
DSES 6180-01 DATA MINING AND KNOWLEDGE DISCOVERY
Instructor:
Prof. Mark J. Embrechts (x 4009 or 371-4562)
Office hrs:
CII 5217 Monday/Thursday 10:00-12:00
Class Time:
Monday/Thursday 4-5:20 pm (Jonson-Rowland Science Center 2C30)
Book: Margaret H. Dunham, Data Mining: Introductory and Advanced Topics, Prentice Hall
2003.
LECTURES #24&25: Intro to Fuzzy Logic
Fuzzy logic is an extension of Boolean logic and is a powerful tool for CI (computational
intelligence) applications and expert systems. Fuzzy logic could and often should be combined
with traditional neural network algorithms. This lecture will explain the basic idea of fuzzy logic
and illustrate some examples how fuzzy logic can be applied to solve problems. Neural networks
can be combined with fuzzy logic in a variety of ways. A recommended book on the subject is:
Fuzzy Engineering
Bart Kosko
Prentice Hall, 1997 (ISBN 0-13-124991-6)
Lotfi A. Zadeh is generally credited with the invention of fuzzy logic. The basis for fuzzy logic
was in a sense anticipated by the philosopher Max Black in 1937 with his concept of threevalued logic. Infinite value logic developed by the Polish mathematician Lukasiewicz in the early
1930s is a generalization of three-valued logic and a predecessor of what Zadeh named fuzzy
logic.
A highly recommended book (and former general bestseller in the UK) that playfully introduces
the reader to fuzzy concepts can be found at www.amazon.com under:
Fuzzy thinking
Bart Kosko
Prentice Hall (1993).
Handouts:
[1] Earl Cox, “Solving problems with fuzzy logic,” AI Expert, pp. 28 - 37 (March 1982).
[2] Lotfi A. Zadeh, “The Calculus of Fuzzy If / Then Rules,” AI Expert, pp. 23-27 (March 1992).
[3] Mark J. Embrechts and Harold W. Lewis, III, “Fuzzy Expert Systems for Data Mining,” in
Intelligent Engineering Systems through Artificial Neural Networks, Vol. 7, Cihan H. Dagli,
Metin Akay, Okan Ersoy, Benito R. Fernandez, and Alice Smith, Eds., pp. 753 - 758, ASME
Press, New York (1997).
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Deadlines:
January 22
January 29
February 16
March 1
March 4
March 18
March 8&11
March 15
April 8
April 19
April 22/26
HW#0 (Web browsing).
Project Proposal
HW #1
Quiz #1 on PLS paper by Svante Wold et al.
HW #2
HW #3
Spring Break
Progress Report
Guest lecture
HW#4
Final Presentations
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