Introduction to Data Mining

 

Course Line Number: 11412

Instructor: Dr. Guozhu Dong

Credit Hours: 4

Email: gdong@cs.wright.edu

Classroom: 105 Biological Sciences

Telephone:  937-775-5066

Class Schedule: 2:15-3:30pm TTH

Office Location: RC 430

 

Office Hours: TBA

 

Course Description

Data mining is concerned with the extraction of novel knowledge from large amounts of data. This course introduces and studies the concepts, issues, tasks and techniques of data mining. Topics include data preparation and feature selection, association rules, classification, clustering, evaluation and validation, scalability, spatial and sequence mining, and data mining applications. The course is suitable for undergraduate senior students and graduate students.

Prerequisites:

CS 400 (Data Structures), CS 405 (Introduction to Database Systems), or CS 409 (Introduction to AI), or equivalent or with consent of the instructor.

 

Homework:

Students will read chapters in the reference book and the class notes. They will also submit a number of homework exercises, which will be graded on the understanding and knowledge of the students.

 

Projects:

Students will perform a number of individual course projects for different Data Mining tasks, like pre-processing, or association mining.

 

Textbook:

Data Mining: Concepts and Techniques
Jiawei Han and Micheline Kamber
Morgan Kaufmman Publishers, 2000

 

Evaluation Methods (tentative):

Homeworks: 10%; Projects: 30%; Midterm: 25%; Final: 35%.