LEC #  Topics  Data Sources 

1 
Data Mining Overview (PDF) Prediction and Classification with kNearest Neighbors Example 1: Riding Mowers (PDF) 
Table 11.1 from page 584 of: Johnson, Richard, and Dean Wichern. Applied Multivariate Statistical Analysis. 5th ed. PrenticeHall, 2002. ISBN: 0130925535. 
2 
Classification and Bayes Rule, Naïve Bayes (PDF) 

3 
Classification Trees (PDF) 
“Housing Database (Boston).” Publicly available data at University of California, Irvine School of Information and Computer Science, Machine Learning Repository of Databases. 
4 
Discriminant Analysis Example 2: Fisher’s Iris data (PDF) 
“Iris Plant Database.” Publicly available data at University of California, Irvine School of Information and Computer Science, Machine Learning Repository of Databases. 
5 
Logistic Regression Case (PDF) Handlooms (PDF) 

6  Neural Nets (PDF)  
7 
Discussion of homework  see Problem 1 in assignments section 

8 
Multiple Regression Review (PDF) 

9 
Multiple Linear Regression in Data Mining (PDF) 

10 
Regression Trees, Case: IBM/GM weekly returns Comparison of Data Mining Techniques (PDF) Discussion of homework  see Problem 2 in assignments section 

11 
kMeans Clustering, Hierarchical Clustering (PDF) 

12 
Case: Retail Merchandising 

13 
Midterm Exam 

14 
Principal Components (PDF) 
Example 1, Head Measurements of Adult Sons: Rencher, Alvin. Methods of Multivariate Analysis. 2nd ed. WileyInterscience, 2002. Table 3.7, p. 79. ISBN: 0471461725. Example 2, Charactersitics of Wine: “Wine Recognition Database.” Publicly available data at University of California, Irvine School of Information and Computer Science, Machine Learning Repository of Databases. 
15 
Guest Lecture by Dr. Ira Haimowitz: Data Mining and CRM at Pfizer 

16 
Association Rules (Market Basket Analysis) (PDF) 
Han, Jiawei, and Micheline Kamber. Data Mining: Concepts and Techniques. Morgan Kauffman Publishers, 2001. Example 6.1 (Figure 6.2). ISBN: 1558604898. 
17 
Recommendation Systems: Collaborative Filtering 

18 
Guest Lecture by Dr. John Elder IV, Elder Research: The Practice of Data Mining 
Lecture Notes
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Spring
2003
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Lecture Notes