EMTM 554: Data Mining

What is data mining? The data mining process. Data visualization. Data mining methods: decision trees, regression, neural nets, clustering, network analysis and feature selection. How the methods work. When to use them. Evaluation of business intelligence systems. Strategic use of information. Emerging data mining methods: text mining. This is a technical elective and will go into detail on the various methodologies, as well as looking at current industry trends. Prerequisite: Statistics and knowledge of JMP.

Administrivia

Course Syllabus
Homework
Textbook
- Data Mining Concepts and Techniques second edition (Han and Kamber)
Professor
- Lyle Ungar (ungar@cis.upenn.edu)
WebCafe
Quiz sample problems and solutions
References
Data sets See in particular the KDD cups and the UCI repository
Software The Course will use JMP.
Grades
- 25% based on the final quiz
- 50% based on homework other than the final project
- 25% based on the final project

Announcements

Pre-assignment due the first day of class is posted as hw1 under the "Homework"
Readings are listed under the day that they are discussed. Unless otherwise specified, you can either read them before or after the lecture.

This page is http://www.cis.upenn.edu/~ungar/DBM/

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ungar@cis.upenn.edu