Navigation
Contact Me
Office: 4423 Engr Building
Office Hours: T 4:00-5:00 pm
rangwala@cs.gmu.edu
703-993-3826
Syllabus
| Instructor: | Huzefa Rangwala, Room #345 ST II, rangwala@cs.gmu.edu |
| Class Time & Location: | IH 105, M 4:30pm - 7:10pm |
| Text Book: | Pang-Ning Tan, Michael Steinbach, and Vipin Kumar Introduction to Data Mining, Addison Wesley, 2006. Book's companion website |
| Teaching Assistant: | Al-Arayed, Dalal , 330/348 ST II, dalaraye@gmu.edu |
| Office Hours: | Instructor: M 3:00-4:00 pm, TA: W: 2:30-4:30pm |
Please note the syllabus is subject to change to enrich the student's learning experience :). Feel free to email rangwala@cs.gmu.edu for questions, concerns, or even say hi
| Course Description |
|---|
| Over the past decade there has been an exponential increase in the amount of data. This has lead to development of techniques to discover useful and interesting information from the large collections of data. This course aims to provide a overview of the key data mining methods and techniques like classification, clustering, and association rule mining. The course will also provide interesting application examples of data mining, especially in the field of bioinformatics and spatial data mining. |
| Course Prerequisites |
| Some programming experience is expected. Students should be familiar with basic probability and statistics concepts, and linear algebra. Please expect some programming in the assignments and class projects. |
| Course Format |
| Lectures will be given by the instructor. Besides material from the textbook, topics not discussed in the book may also be covered. Research papers and handouts of material not covered in the book will be made available. Grading will be based on homework assignments, exams, and a project. Homework assignments will require some programming. Exams and homework assignments must be done on an individual basis. Any deviation from this policy will be considered a violation of the GMU Honor Code. |
| Course Outcomes |
As an outcome of taking this class, a student will be able to
|
| Date | Topics Covered | |
|---|---|---|
| 08.25.2008 |
Welcome, Introduction to Data Mining (Chapter 1) Data (Chapter 2) |
|
| 09.01.2008 | Labor Day (No Class) | |
| 09.08.2008 |
Data Contd. (Chapter 2) Warehousing and Exploration (Chapter 3) |
|
| 09.15.2008 |
Classification (Chapter 4) Classification (Chapter 5) |
|
| 09.22.2008 |
JIgsaw Activity (Classification Algorithms) Bioinformatics Example (Fold Recognition) |
|
| 09.29.2008 | Clustering (Chapter 7) | |
| 10.6.2008 |
Mid Term 1 Clustering (Chapter 8) |
|
| 10.13.2008 | Clustering ( Chapter 8) | |
| 10.20.2008 | Association Rule Mining (Chapter 6) | |
| 10.27.2008 | Outlier Detection Mining (Chapter 10) | |
| 11.3.2008 | Outlier Detection Mining (Chapter 10) | |
| 11.10.2008 | Data Mining in Bioinformatics | |
| 11.17.2008 |
Mid Term 2 Spatial Data Mining | |
| 11.24.2008 | Project Presentations I | |
| 12.01.2008 | Guest Lecture (Dr. Carlotta) | |
| 12.08.2008 | Project Presentations II | |
| 12.15.2008 | No Final :) |
| Deadline | Type | % Weight |
|---|---|---|
| 09.22.2008 | Assignment 1 | 10 |
| 10.6.2008 | Mid-Term Exam 1 | 20 |
| 10.13.2008 | Assignment 2 | 10 |
| 11.10.2008 | Assignment 3 | 10 |
| 11.17.2008 | Mid-Term Exam 2 | 20 |
| 12.08.2008 | Final Project* (See Below for Milestones) | 30 |
| 10.20.2008 | Project Proposal (2 pages) | 5 |
| Signup | Project Presentations | 10 |
| 12.08.2008 | Final Report | 15 |
* Note: There will be no extensions offered for the project. I would encourage you to start early.
| Grade | Score Range |
|---|---|
| A+ | >97 |
| A | 92-97 |
| A- | 88-92 |
| B+ | 84-88 |
| B | 80-84 |
| B- | 76-80 |
| C+ | 72-76 |
| C | 68-72 |
| C- | 64-68 |
| F | < 64 |
| Attendance |
|---|
| Attendance is not compulsory but highly recommended for doing well in the class. This class has lots of active learning exercises, and they will be a lot of fun. |
| Assignment Submission |
| Please ensure that the assignments are submitted on-time. No late submissions. |
| Make-Up Exams & Incompletes |
| Make up exams and incompletes will not be given for this class. |
| Academic Honesty and GMU Honor Code |
| Please visit the University's Academic Honesty Page and GMU Honor Code . |
| Disability Statement |
| If you have a documented learning disability or other condition that may affect academic performance you should: 1) make sure this documentation is on file with the Office of Disability Services (SUB I, Rm. 222; 993-2474; www.gmu.edu/student/drc) to determine the accommodations you need; and 2) talk with me to discuss your accommodation needs. |
User login
News Highlights
- Syed F to join the Lab.
- Paper Accepted at Journal of Chemical Information & Modeling
- Huzefa to serve on program committee for SIAM Data Mining Conference 2010 (SDM 2010)
- Huzefa to serve on program committee for HiCOMB 2010
- New funding received from NSF IIS for bridging chemical and biological spaces.
- Two open positions for graduate students (MLBio+ Laboratory)
- Ammar submits his 1st paper!
- Salman's paper accepted at WISM-AICI 2009.
- Huzefa presents 2 posters at ISMB 2009
- Sheng Li and Anveshi join the lab this Fall
Bioinformatics & Data Mining
- PrePrint: Skewed Rotation Symmetry Group Detection
- PrePrint: Object Detection with Discriminatively Trained Part Based Models
- PrePrint: Large Scale Discovery of Spatially Related Images
- PrePrint: Epitomic Location Recognition
- PrePrint: Class Conditional Nearest Neighbor for Large Margin Instance Selection