Date Class Period & Lecture Topic Reading Assignment
Jan 06 1. Syllabus and Introduction    
Jan 08 2. Classification/Regression Linear Regression Tutorial (S. Waner, Hofstra University),
Simple Logistic Regression (R. Lowry, Vassar College)
Wiki Assignment
Jan 13 3. Clustering Clustering (M.H. Dunham, Data Mining: Introductory and Advanced Topics, Pearson Education Inc., 2003, Chapter 5): Sections 5.1-5.5.5  
Jan 15 4. Correlation Apriori (P-N. Tan, M. Steinbach and V. Kumar, Introduction to Data Mining, Pearson Education Inc., 2006, Chapter 6): Sections 6.1-6.3; some possibly helpful slides (C. Giraud-Carrier and D. Norton, Brigham Young University) Linear Models
Jan 20 5. Data-driven Model Construction    
Jan 22 6. The ML/DM Process Data Mining Methodology: The Virtuous Cycle Revisited (M.J.A. Berry and G.S. Linoff, Mastering Data Mining, Wiley, 2000, Chapter 3) Clustering
Jan 27 7. No Lecture Contribute a Group Project Idea -- See the Wiki  
Jan 29 8. WEKA Overview Machine Learning with WEKA (E. Frank, University of Waikato, New Zealand) Apriori
Feb 03 9. Intro to Group Project    
Feb 05 10. Feature selection (PCA) A Tutorial on Principal Components Analysis (L. I. Smith, University of Otago, New Zealand) WEKA exercise
Feb 10 11. Error and other utility measures Evaluation of models (parts 1 and 2) (Data Mining Tutorial, Rudjer Boskovic Institute),
Confusion Matrix (H.J. Hamilton, Online Notes for CS 831, University of Regina, Canada),
ROC Graph (H.J. Hamilton, Online Notes for CS 831, University of Regina, Canada)
Feb 12 12. Instance-based Learning Instance-Based Learning (Tom M. Mitchell, Machine Learning, McGraw Hill, 1997, Chapter 8): Sections 8.1-8.4 Report: Objectives, Requirements, Plan
Feb 17 13. No Lecture (Monday Instruction)    
Feb 19 14. Review/Grad School   WEKA Lab 1
  Midterm (Feb 23–25 in the testing center)
Feb 24 15. No Lecture (Midterm)    
Feb 26 16. Decision Trees Decision Tree Learning (Simon Colton, Imperial College, London) Report: Initial Data
Mar 03 17. Multi-layer Perceptrons Multi-Layer Artificial Neural Networks (Simon Colton, Imperial College, London)  
Mar 05 18. Multi-layer Perceptrons   Report: Final Data
Mar 10 19. Support Vector Machines Support Vector Machines (Marti Hearst, IEEE Intelligent Systems, pp. 18-28, July/August 1998 -- focus on first 3.5 pages)  
Mar 12 20. Support Vector Machines    
Mar 17 21. Model Selection Paired Permutation Test Modeling
Mar 19 22. Bias/Variance    
Mar 24 23. Ensembles Experiments with a New Boosting Algorithm (Yoav Freund and Robert E. Shapire, Proceedings of the International Conference on Machine Learning, pp. 148-156,1996) Report: Verification
WEKA Lab 2
Mar 26 24. Association Mining    
Mar 31 25. Artificial Ethics? Brave New Era for Privacy Fight (Wired, 13 January 2005),
In Age of Security, Firm Mines Wealth of Personal Data (Washington Post, 20 January 2005),
ChoicePoint: We're Sorry for Data Leak (CNET News, 15 March 2005),
Can Data Mining Catch Terrorists? (Information Week, 22 May 2006),
U.S. Doctors Object to Data-Mining (Herald Tribune, 4 May 2006)
Apr 02 26. Creative Intelligent Systems    
Apr 07 27. Oral Presentations Music Group, Robot Group, Road Group  
Apr 09 28. Oral Presentations Speech Group, Library Group, Quiz Group, Talks Group  
Apr 14 29. Review   Group Project Report
Apr 16 Reading Day    
Apr 17 Final (7:00am–10:00am in class)