Class Information
| Instructor: |
Huzefa Rangwala, Room #4423 EB, rangwala@cs.gmu.edu |
| Class Time & Location: |
AB 2026, M 7:20pm - 10:00pm |
| Text Book: |
Pang-Ning Tan, Michael Steinbach, and Vipin Kumar Introduction to Data Mining, Addison Wesley, 2006. Book's companion website |
| Teaching Assistant: |
None
|
| Office Hours: |
Instructor: M 3:00-5:00 pm, TA: TBD |
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
If you have taken INFS 755, then you will not receive credit for CS 750
About the Course
| 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. If you are not sure about the pre-reqs send me an email.
|
| 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
- Understand the various classification, clustering, association rule-mining algorithms.
- Apply the data mining techniques learned to real world applications.
- Read research papers pertaining to data mining and cloud computing
|
Schedule
| 01.24.2011 |
Welcome, Introduction to Data Mining (Chapter 1) |
|
| 01.31.2011 |
Data (Chapter 2) |
|
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02.07.2011
|
Classification (Chapter 4 & 5)
|
[HW1 out]
|
|
02.14.2011
|
Classification (Contd), Bioinformatics Example
|
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02.21.2011
|
Clustering (Chapters 7 & 8)
|
[HW 1 due]/[HW2 out]
|
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02.28.2011
|
Clustering (Contd.)
|
|
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03.07.2011
|
Association Rule Mining (Chapter 6)
|
[HW2 due]
|
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03.14.2011
|
No Class [Spring Break]
|
|
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03.21.2011
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Jigsaw Activity: Clustering
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[Proposal Due]
|
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03.28.2011
|
Exam [30%]
|
[HW3 out]
|
|
04.04.2011
|
Outlier Detection (Chapter 10)
|
|
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04.11.2011
|
Web Mining Example
|
[HW3 due]
|
|
04.18.2011
|
Spatial Data Mining
|
|
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04.25.2011
|
Cloud Computing
|
|
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05.02.2011
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Project Presentations
|
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05.16.2011
|
Project Reports Due [NO Final]
|
|
Assignments/Exams
| Deadline
| Type
| % Weight |
| 02.21.11 |
HW 1 |
10 |
| 03.07.11 |
HW 2 |
10 |
| 04.11.11 |
HW 3 |
10 |
| 03.28.11 |
Exam |
30 |
| - |
Class Participation |
5 |
| |
Project |
35 |
| 03.21.11 |
Project Proposal (2 pages) |
5 |
| 05.02.11 |
Project Presentations |
10 |
| 05.16.11 |
Final Report |
20 |
Grade Distribution
| Grade
| Score Range |
| A+ |
>98 |
| A |
94-98 |
| A- |
90-94 |
| B+ |
86-90 |
| B |
82-86 |
| B- |
78-82 |
| C+ |
74-78 |
| C |
70-74 |
| C- |
66-70 |
| F |
< 66 |
Policies:
| 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. |
