CSE 4510/5400-E6: Data Mining
Spring 2016, MW 5-6:15pm, Quad 117
Philip Chan
322 Harris Center, 674-7280
Office Hours: MW 1-3pm (or by appointment)
Course WWW Page: http://cs.fit.edu/~pkc/classes/dm/
The wide adoption of computational devices has created opportunities
for discovering interesting information that can further help improve
our lives. We will discuss algorithms for analyzing data to extract
patterns for classification, association, clustering, and anomaly
detection. We will also discuss some of the applications such as spam
detection as classification, customer buying behavior as association,
identifying cancer subtypes as clustering, identifying novel events as
anomaly detection.
Textbook
Tan, Steinbach, and Kumar (2006). Introduction to Data Mining, Addison Wesley.
Topics
- Introduction (Ch 1)
- Classification (Ch 4 and 5.1)
- Association (Ch 6)
- Clustering (Ch 8)
- Anomaly Detection (Ch 10)
Important Dates (Assignment due dates might be adjusted due to circumstances)
| Last day to drop |
Jan 22 (Fri) |
| HW1 |
Feb 3 (Wed) |
| HW2 |
Feb 24 (Wed) |
| Midterm exam |
Mar 2 (Wed) [tentatively] |
| HW3 |
Mar 16 (Wed) |
| Last day to withdraw |
Mar 18 (Fri) |
| HW4 |
Apr 6 (Wed) |
| HW5 |
Apr 27 (Wed) |
| Final exam |
May 2 (Mon), 6-8pm |
Evaluation
- Homework Assignments (50%) [programming and written]
- Midterm exam (20%), Final exam (30%)
Policies
- Students are encouraged to help each other on assignments,
but plagiarism (copying) is prohibited.
- first violation: zero on assignment/test
- second violation: 'F' for the course
- Late assignments are accepted, but 20% is deducted for each day.
- Documentation constitutes 10% of each programming assignment.
Prerequisite
- CSE 2010 Algorithms and Data Structures ["C" or above]