Data Mining

Calendar

LEC #	Topics	Key Dates
Introduction
1	Data Mining Overview, Prediction and Classification with k-Nearest Neighbors
Classification
2	Classification and Bayes Rule, Naïve Bayes
3	Classification Trees	Homework 1 out
4	Discriminant Analysis
5	Logistic Regression Case: Handlooms
6	Neural Nets
7	Cases: Direct Marketing/German Credit	Homework 1 due Homework 2 out
Prediction
8	Assessing Prediction Performance
9	Subset Selection in Regression
10	Regression Trees, Case: IBM/GM weekly returns	Homework 2 due
Clustering
11	k-Means Clustering, Hierarchical Clustering
12	Case: Retail Merchandising
13	Midterm Exam
Dimension Reduction
14	Principal Components
15	Guest Lecture by Dr. Ira Haimowitz: Data Mining and CRM at Pfizer
Data Base Methods
16	Association Rules (Market Basket Analysis)
17	Recommendation Systems: Collaborative Filtering
Wrap Up
18	Guest Lecture by Dr. John Elder IV, Elder Research: The Practice of Data Mining
19	Project Presentations