|
|
CSCE 5380 Data Mining
Instructor: Dr. Yan Huang
Fall 2009
|
|
|
|
|
|
Announcements
·
11/05,
assignment 3 has been posted and will be due Nov.
24 before class.
·
11/04,
Exam III will be on Dec. 03 and will cover clustering and association
mining.
·
11/04,
Lab II is posted and will be due Nov. 24
before class.
·
10/19,
project is posted and due Dec. 07.
·
10/06,
Lab I is posted and will be due Oct. 27
before class.
·
10/06,
this Thursday’s class will be in Room 140 for a Weka demo.
·
10/05,
Exam II will be on Nov. 3, and covers chapter 4 and chapter 5 of the book.
·
10/05,
assignment 2 has been posted and will be due
Oct. 27 before class.
·
09/22,
Exam I will be on Oct. 1 and will cover the first three chapters of the
book. You can have one-page cheating sheet (one side only) with any font
size.
·
09/12,
assignment 1 has been posted and will be due
09/24 before class.
·
09/01,
the teaching assistant’s office hours have been changed to Fridays 2:00pm –
6:00pm.
·
08/25,
Welcome to the data mining class!
|
|
|
|
|
|
Syllabus
[pdf]
|
Instructor:
|
Dr. Yan Huang
|
|
Office:
|
Research Park, F251, tel:
940-369-8353
|
|
Email:
|
huangyan ‘at’ cs.unt.edu
|
|
Class hours:
|
TTh 11:00am -12:20pm, Research
Park B192
|
|
Office hours:
|
TTh 09:00am- 10:00am
|
|
|
|
|
Teaching assistant:
|
Roopa Vishwanathan
|
|
Office:
|
F205
|
|
Email:
|
RoopaVishwanathan@my.unt.edu
|
|
Office hours:
|
Fridays
2:00pm to 6:00 p.m.
|
|
|
|
|
|
|
|
Course description:
|
This course will provide a broad and rapid
introduction to the field of data mining. We will provide a general
introduction to main data mining tasks, e.g. classification, clustering,
association rules, and outlier detection, and some of the latest
developments, e.g. mining spatial data and web data.
|
|
|
|
|
|
|
Class Notes
·
Notes from
the book author’s website
|
|
|
|
|
|
Assignments
·
Assignment
3.
·
Lab II.
·
Project.
·
Lab I.
·
Assignment
2.
·
Assignment
1.
|
|
|
|
|
|
Books
Required textbook
|
|
Introduction to Data Mining
Pang-Ning Tan,
Michigan State University
Michael Steinbach, University of Minnesota
Vipin Kumar, University of Minnesota
ISBN:
0-321-32136-7
Publisher: Addison-Wesley
Buy this book (new) from Amazon.
Compare prices (new or used) at BestBookBuys
|
Recommended readings
- J. Han and M. Kamber
(2000) Data Mining: Concepts
and Techniques , Morgan Kaufmann
- U.
M. Fayyad, G. Piatetsky-Shapiro, P. Smyth, R. Uthurusamy, Advances in Knowledge Discovery and
Data Mining, The MIT Press, 1996
- U.
Fayyad, G. Grinstein, and A. Wierse, Information Visualization in Data Mining and Knowledge
Discovery, Morgan Kaufmann, 2001
- D.
J. Hand, H. Mannila, and P. Smyth, Principles of Data Mining, MIT Press, 2001.
- T.
Hastie, R. Tibshirani, and J. Friedman, The Elements of Statistical Learning: Data Mining,
Inference, and Prediction, Springer-Verlag, 2001
- T.
M. Mitchell, Machine Learning,
McGraw Hill, 1997.
- S.
M. Weiss and N. Indurkhya, Predictive
Data Mining, Morgan Kaufmann, 1998
- H.
Witten and E. Frank, Data
Mining: Practical Machine Learning Tools and Techniques with Java
Implementations, Morgan Kaufmann, 2001
|
|
|
|
|
|
|
Links
1. The book authors’ website
2. UCI Machine
Learning Data Repository
|
|
|