COSC 4335 - Data Mining

Dr. Rakesh Verma
Email: Find it here
Office 532 PGH, Ph: 743-3348
Office Hours for Spring 12: Tu./Th. 1.15-1.45pm (or by appt.)

» syllabus

Download

• Adobe PDF

Prerequisites

Math 3336 and COSC 3380. Discuss with instructor if you are missing prerequisites.

Books and References

Textbook

• Introduction to Data Mining - P.-N. Tan, M. Steinbach and V. Kumar, Pearson Education, Inc., 2006.

References

• Data Mining: Concepts and Techniques - J. Han and M. Kamber, Morgan Kaufmann, Second edition, 2005.
• TBA.

Goals

To provide computer science students with a broad understanding of various data mining techniques, algorithms, and applications.

Topics

• Introduction to Data Mining
• Data: Types, Quality, Preprocessing, Measures of Similarity and Dissimilarity
• Exploring Data
• Classification - Basic Concepts
• Association Analysis
• Clustering
• Anomaly Detection
• Advanced Concepts - As time permits

Academic Honesty Policy

Assistance of or Collaboration with any animate or inanimate object (except the instructor and the TAs) is completely disallowed on all exams and projects; any violation will be severely penalized with the minimum penalty on FIRST violation being an F grade.

Grading (subject to change)

• Class participation and Motivation - 5% and 4% respectively
• Homeworks - 6%
• Quiz 1 (in class) - 15%
• Quiz 2 (in class) - 25%
• Project - 45%