1 | Data Mining Overview (PDF) Prediction and Classification with k-Nearest Neighbors
Example 1: Riding Mowers (PDF) | Table 11.1 from page 584 of: Johnson, Richard, and Dean Wichern. Applied Multivariate Statistical Analysis. 5th ed. Prentice-Hall, 2002. ISBN: 0-13-092553-5. |
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 | k-Means 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. Wiley-Interscience, 2002. Table 3.7, p. 79. ISBN: 0-471-46172-5.
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: 1-55860-489-8. |
17 | Recommendation Systems: Collaborative Filtering | |
18 | Guest Lecture by Dr. John Elder IV, Elder Research: The Practice of Data Mining | |