CSCE 566/CMPS 499: Data Mining

Spring 2018 (1/10 - 4/27)

Time/Location: TR 9:30am - 10:45am, Oliver 116
Office hours: TR 11am - 12 noon, Oliver 222D

Xindong Wu
Teaching Assistant

Ege Beyazit

One-semester programming in Java (or C++).
One-semester statistics/probability.
Additional References

Course Description

Data mining is a broad area that integrates techniques from several fields including machine learning, statistics, pattern recognition, artificial intelligence, and database systems, for the analysis of large volumes of data. This course gives a wide exposition of these techniques and their software tools. Topics include: association analysis, classification, clustering, pattern discovery in sequential data, and Bayesian networks.

Advanced Topics for PhD Comprehensive Exams
Grading Policy (in Spring '18)

Two Assignments: C4.5 due Feb. 8 and Weka due on Feb. 22 10%
Mid-Term Exam (close-book and close-notes): Mar. 15 30%
Paper Presentations (for CSCE 566 students only)  10%
Class Quizzes 10%
Essay (for CSCE 566 students only) 10%
Final Exam (close-book and close-notes): May 3, 8:00am - 10:30am, Oliver 116 30%

Course Syllabus by Chapter

Useful Links

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