CS 535 Introduction to Data Mining Fall 2008
Goals:
This data mining course introduces concepts, algorithms, techniques, and
applications of data mining. Topics include background of data mining, data
preprocessing, classification, clustering, associationrules mining. This
course is designed for CS graduate students.
Class Schedule: T TH 4:25 PM  5:50 PM 
Classroom: EB G7 
Instructor: Dr. Lei Yu 
TA: Yue Han 
Telephone: (607) 7776250 

Email: lyu AT cs DOT 
Email: yhan1 AT 
Office Location: G16,

Office Location: N1,

Office Hours: T TH 12:30PM  1:30PM or by appointment 
Office Hours: T TH 2:00PM  3:00PM 
Prerequisite:
Topics:
Textbook:
Homework:
There will be 4 written assignments.
Project:
There will be a group (of two or three students) project involving implementation of decision tree algorithm and standard model selection procedure.
Examinations:
There will be several quizzes and two exams in class.
Grading:
Final grades will be based on quiz (10%), homework (4 assignments, 20%), Exam I (25%), Exam II (25%), project (20%).
Academic Integrity:
Discussion of general concepts and questions concerning the homework
assignments among students is encouraged. However, each of you is expected
to work on the homework solutions on your own. Sharing of any part of
solutions is prohibited. If you are unclear about the policy, please consult
with the instructor before you act. Suspected cases of academic
misconduct will be pursued fully in accordance to the
Student Academic Honesty
Code of
Late Policy:
Each assignment is due at the beginning of class on the due date. Any
assignment received within the next 24 hours will be penalized by 20% of the
full credit; any assignment received within the time between 24 hours and 48
hours pass the deadline is penalized by 50% of the full credit; No assignment
will be accepted after 48 hours pass the deadline. Rare exceptions of this
policy may be made at the discretion of the instructor under demonstrably
circumstances.

Last updated on 09/02/2008 