Data Mining Course

CSCI-4390/6390 Data Mining

Fall 2004

Contact Information

Instructor:	Mohammed J. Zaki
Office:	Lally 307
Phone:	x6340
Email:	zaki.AT.cs.rpi.edu
Class Hours:	Room CARNEGIE 106, MR 10:00-11:50am
Office Hours:	Mondays 12-2pm, or by appointment
Web Page:	http://www.cs.rpi.edu/~zaki/dmcourse/
TA Info:	Zujun Shentu (shentu@cs.rpi.edu) Office Hours: 2:30pm-4pm TF in Science Center, Bray Room, 1W01

Course Link from Fall03

Course Information

Syllabus

Paper List

Groups

Announcements

12/17/04: Your final grades are HERE
12/3/04: Exam2 and its solution are now posted.
11/26/04: Project deadline moved to 5th Dec, 11:59pm. Please submit the source code via email to Zujun, and bring a hard copy of the report to class on 6th. We will have 4-5 group presentations (in the order of group number) on 6th and the remaining on 9th. Each group should prepare a 20min presentation using overhead projector/blackboard. Highlight the problem, the solutions, the challenges, the results and comments on the future improvements.
11/26/04: Solutions to both HW3 and HW4 are now posted.
11/12/04: HW4 is now posted. It is due on November 22nd, before class ends.
11/11/04: Q3b on HW3, can be submitted directly to Zujun in his mailbox in AE119. You can assume attribute independence to solve the EM problem.
There will be no new material for class on 15th. Instead Zujun will answer any questions you have on material since previous exam.
11/3/04: HW3 is now posted. It is due on November 11th, before class ends.
11/2/04: Exam1 and its solution are now posted.
10/13/04: Solutions to both HW1 and HW2 are now posted.
10/5/04: Group Project description is now available. The final project is due on Friday 12th November. Please email your project preferences to Zujun and me by 7th October.
10/5/04: HW2 is now posted. It is due on October 12th, before class ends.
9/26/04: HW1 is now posted. It is due on October 4th. Send in your code to the TA directly via email. The hard-copy HW should be submitted before class ends.

Class Topics

MONDAYS	THURSDAYS
Aug 30 – Overview	Sep 2 – Exploratory Data Anaysis (EDA)
Sep 6 – NO CLASS (labor day)	Sep 9 – EDA
Sep 13 – Computational Statistics	Sep 16 – Pattern Mining
Sep 20 – Set Mining	Sep 23 – Set Mining
Sep 27 – Sequence Mining	Sep 30 – Tree & Sequence Mining
Oct 4 – Suffix Trees	Oct 7 – Tree & Graph Mining
Oct 12 (Tuesday) – Review	Oct 14 – EXAM I
Oct 18 – Graph Mining	Oct 21 – Clustering
Oct 25 – Clustering	Oct 28 – Clustering
Nov 1 – Clustering	Nov 4 - Classification
Nov 8 – Classification	Nov 11 – Classification
Nov 15 – Review Session	Nov 18 – Classification
Nov 22 – Classification	Nov 25 – NO CLASS (thanksgiving)
Nov 29 – EXAM II	Dec 2 – Outlier detection
Dec 6 – Project Presentations	Dec 9 – Project Presentations