Steam-powered Turing Machine University of Washington Department of Computer Science & Engineering
 CSE 574 - Artificial Intelligence II - Winter 2000
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Data Mining and Machine Learning

Instructor: Pedro Domingos
Office: Sieg 216
Office hours: Thursday 11:00-12:00 and by appointment
TA: Geoff Hulten
Office: 104 Chateau
Office hours: ?? and by appointment

Class meets: TuTh 12:00-1:20 EE1 026



Students will do a project and give a seminar. Projects can be done individually or in groups of two, and are due on the last day of classes (March 9). Projects can be chosen from the list below, or proposed by the students. The seminar may be on a topic related to the project, or not. Seminars are Pass/Fail; a Pass is required to complete the class. The class grade will be the project grade.




Week 1: Chapter 1 of Fayyad, Chapter 1 of Mitchell, paper by John
Week 2: Paper by Domingos, Chapter 3 of Mitchell
Weeks 3 & 4: Chapter 10 of Mitchell, Chapter 5 of Fayyad
Week 5: Chapter 8 of Mitchell, Section 2 of paper by Dietterich
Week 6: Chapter 4 of Mitchell
Week 7: Chapter 6 of Mitchell, Chapter 11 of Fayyad

Lecture Notes

Week 1: Introduction
Week 2: Decision trees: Part 1 and Part 2
Weeks 3 & 4: Rule induction
Week 5: Nearest neighbor, model ensembles
Week 6: Neural networks: Part 1 and Part 2
Week 7: Bayesian networks: Part 1 and Part 2


Tu Feb 22: Sarah & Steve (data cleaning)
Th Feb 24: Richard (pruning adaptive boosting, knowledge discovery via multiple models) & Ana-Maria (learning with concept drift and hidden context)
Tu Feb 29: Corin (intrusion detection) & Mike (support vector machines)
Th Mar 2: Matt (hidden Markov models), Vassili & Alex (discovering frequent episodes in sequences)
Tu Mar 7: Ashish & Deepak (causal discovery)
Th Mar 9: AnHai (text classification) & Yongshao (error-correcting output codes)

Project Ideas

Mail Archive

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University of Washington
Box 352350
Seattle, WA  98195-2350
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