HOME

News & Announcements

9/4: HW1 posted. Due date 9/15.

9/18: HW2 posted. Due date 9/24.

10/2: HW3 posted. Due date 10/15. Datasets are available here.

10/4: Project Guidelines posted. Proposal due date 10/27.

10/23: HW4 posted. Due date 11/12.

11/4: HW4 due date postponed to 11/17.

11/17: HW5 posted. Due date 11/24.

12/4: Final topics

12/5: HW5 solution posted on Blackboard.

Course Description

Basic principles and methods for data analysis and knowledge discovery. Emphasizes developing basic skills for modeling and prediction, on one side, and performance evaluation, on the other. Topics include system design; data quality, preprocessing, and association; event classification; clustering; biometrics; business intelligence; and mining complex types of data.

Instructor:

Dr. Jessica Lin

Office: Engineering Building 4419
Phone: 703-993-4693
Email: jessica [AT] cs [DOT] gmu [DOT] edu
Office Hours: Wednesday 2-3pm, Thursday 1:30-2:30pm

Jatin Mistry
jmistry2 [AT] gmu [DOT] edu
Office Hours: Monday/Tuesday 3-4pm
Location: Engineering Building 5321

Classes

Tuesday/Thursday
12-1:15pm
Art & Design Building 2026

Course Outcomes

The ability to apply computing principles, probability and statistics relevant to the data mining discipline to analyze data.
A thorough understanding of model programming with data mining tools, algorithms for estimation, prediction, and pattern discovery.
The ability to analyze a problem, identifying and defining the computing requirements appropriate to its solution: data collection and preparation, functional requirements, selection of models and prediction algorithms, software, and performance evaluation.
The ability to understand performance metrics used in the data mining field to interpret the results of applying an algorithm or model, to compare methods and to reach conclusions about data.
The ability to communicate effectively to an audience the steps and results followed in solving a data mining problem (through a term project)

Prerequisites:

Grade of C or better in CS 310 and STAT 344

Grading

Assignments: 20%
Project: 20%
Midterms: 30%
Final: 30%

Exams

There will be two midterm exams and a final exam covering lectures and readings (both will be in class, closed book). The final exam is comprehensive. Exams must be taken at the scheduled time and place, unless prior arrangement has been made with the instructor. Missed exams cannot be made up.

Honor Code Statement

The GMU Honor Code is in effect at all times. In addition, the CS Department has further honor code policies regarding programming projects, which are detailed here. Any deviation from the GMU or the CS department Honor Code is considered an Honor Code violation.

Textbooks

Required: Introduction to Data Mining by Pang-Ning Tan, Michael Steinbach, and Vipin Kumar

Recommended: Data Mining and Analysis by Mohammed Zaki (Here is the online pdf version.)

Topics

Ch.1: Introduction
Ch.2: Data
Ch.4: Classification
Ch.5: Classification: Alternative Techniques
Ch.6: Association Analysis: Basic Concepts and Algorithms
Ch.7: Association Analysis: Advanced Concepts
Ch.8: Cluster Analysis: Basic Concepts and Algorithms
Ch.9: Cluster Analysis: Additional Issues and Algorithms
Ch.10: Anomaly Detection

Tentative Schedule

No	Dates	Topics	Reading	Due	Notes
1	9/1 9/3	Introduction 1 Introduction 2	Ch. 1		HW1 posted (due 9/15)
2	9/8 9/10	Data 1 Data 2	Ch. 2
3	9/15 9/17	Classification 1 Classification 2	Ch. 4	HW1 due	HW2 posted (due 9/24)
4	9/22 9/24	Classification 3 Classification 4 / Exercise		HW2 due
5	9/29 10/1	Midterm 1 Classification 5 (updated 10/7)	Ch. 4.5		HW3 and project guideline posted
6	10/6 10/8	Post-midterm review / Classification 5 Classification 6	Ch. 5.2-5.7
7	10/13 10/15	No Class Classification 7		HW3 due
8	10/20 10/22	Clustering 1 Clustering 2	Ch. 8.1 Ch. 8.2		HW4 posted
9	10/27 10/29	Clustering 3 Clustering 4	Ch. 8.3	Proposal
10	11/3 11/5	Midterm 2 Clustering 5	Ch. 8.4
11	11/10 11/12	Clustering 6 Association Analysis 1	Ch. 8.5 Ch. 6.1
12	11/17 11/19	Association Analysis 2 con't	Ch. 6.2-6.3	HW4 due	HW5 posted
13	11/24 11/26	Review No class (Thanksgiving)		HW5 due
14	12/1 12/3	Association Analysis 3 Anomaly Detection / Review	Ch. 6.4, 5, 7 Ch. 10
15	12/8 12/10	Final Exam (note the new date!) Project Presentations
16	12/15 12/17	No class Presentations (10:30am - 1:15pm)		Project report