Steam-powered Turing Machine University of Washington Department of Computer Science & Engineering
 CSE P546 Data Mining - Spring 2010
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Instructor: Jesse Davis
Office: CSE 356
Office hours: Mondays 5:30-6:20, and by appointment
TA: Andrey Kolobov
Office: CSE 216
Office hours: Mondays 5:30-6:20, and by appointment

Class meets:
Mondays 6:30-9:20 in EEB 037


Week Topics Reading Lecture Notes
Week 1 (Mar 29) Introduction; Inductive learning, Instance-based learning Mitchell, Chapters 1, 2 and 8.2 pdf, pptx
Week 2 (Apr 5) Decision trees; Empirical evaluation Mitchell, Chapters 3 and 5 pdf
Week 3 (Apr 12) Bayesian Learning Mitchell, Chapter 6 pdf
Week 4 (Apr 19) Rule Induction Mitchell, Chapter 10 pdf
Week 5 (Apr 26) Neural networks Mitchell, Chapter 4 pdf
Week 6 (May 3) Genetic algorithms, model ensembles Mitchell, Chapter 9 pdf
Week 7 (May 10) SVMs; Learning theory Mitchell, Chapter 7 pdf
Week 8 (May 17) Clustering Chapters 16 and 17 pdf
Week 9 (May 24) Association rules This pdf
Week 10 (May 31) Memorial Day - No Class    


There will be four to five homework assignments, all to be done individually. Assignments are due by the start of class. Each homework will be weighted equally when calculating the final grade. The late turn-in policy is: 10% penalty per day late, up to a maximum of one week.

Schedule Assignment # of Points Topic Additional Info
Due 6.30 p.m., April 12#1100Collaborative Filtering, IBL, D-trees, Methodology 
Due 6.30 p.m., April 26#2100Rule Induction and Bayesian Learning 
Due 6.30 p.m., May 10#3110Voted Perceptron, Ensemble methods, Genetic Algorithms  
Due 6.30 p.m., June 1st#4100Learning theory, SVMs, clustering, association rules  

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CSE logo Department of Computer Science & Engineering
University of Washington
Box 352350
Seattle, WA  98195-2350
(206) 543-1695 voice, (206) 543-2969 FAX
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