CS 594
Main
Menu

Home Page
Syllabus
Pledge
Textbook
Assignments
Links
Instructor

CS 594/494 - Data Mining Practices and Principles
Spring Semester 2006, Section 002
 

TextBook: Introduction to Data Mining
by Pang-Ning Tan, Michael Steinbach, and Vipin Kumar (Addison Wesley, 2006); ISBN: 0-321-32136-7.

Prerequisites: CS302, and CS311 (or their equivalents) or permission of the instructor.

Grades: Points are awarded throughout the term for performance on selected homework problems (25%), the midterm (25%), the course project (30%), and the final exam (20%). Percentages denote portion of final grade attributed to each item. This distribution of points is subject to change.

Please note that under no circumstances will cheating be tolerated. Enrolled students must submit a signed honor pledge statement before submitting any work for grading.

Intent: This course provides a comprehensive introduction to the field of data mining. Topics covered include data preprocessing, predictive modeling, association analysis, clustering, classification, and anomaly detection.

Week(s) Topic Covered = completed
1 Introduction Covered
2-4 Data Covered
5-7 Classification Covered
8-10 Association Analysis Covered
11-13 Clustering Analysis Covered
14 Anomaly Detection
15-16 Course Projects