The
of
Course Description
Data mining plays an increasing role in financial industry, retail industry, Internet services, and ebusiness. It integrates techniques from databases, machine learning, artificial intelligence, statistics, and visualization to discover implicit and useful knowledge from large datasets.
The course will provide a comprehensive introduction to data mining, various data mining techniques, and some successful applications. The emphasis is on modern approaches such as decision tree learning, Bayesian learning, clustering, and association learning. Real-world applications with data mining algorithms and tools will be emphasized.
Prerequisites : Computer Science 319a/b and 346a/b; Statistical Sciences 222a/b or 241a/b or
Biology 244a/b.
Unless you have either the requisites for this course or written special permission from your Dean to enroll in it, you will be removed from this course and it will be deleted from your record. This decision may not be appealed. You will receive no adjustment to your fees in the event that you are dropped from a course for failing to have the necessary prerequisites.
Instructor :
Dr. Charles Ling, Professor
Email: cling@csd.uwo.ca (best way to contact me)
Office Hours: Mondays 2:00 – 4:00 pm. Office: MC 28C.
Textbook : Data Mining: Practical Machine Learning Tools and Techniques, Second Edition (Morgan Kaufmann), by Ian H. Witten, Eibe Frank. 2005.
General Course Conduct
•
Course Website: www.csd.uwo.ca/faculty/ling/cs412
Lecture notes, assignments, and class information will be posted at this site. You are responsible for reading the course website frequently.
•
Student Evaluation : One assignment (20%) and one project (40%), with tentative due dates of 3/3 and 4/7 respectively, and an in-class midterm (40%, tentative date: 3/17). There is no final exam for this course.
Late penalty: 20% each day days after the due date. (Therefore, 5 days after the due date the assignment will worth 0.)
If for any reason the assignment schedule cannot be adhered to, the assignment marks will be pro-rated.
•
A great open-source data mining tool, WEKA, developed by the authors of the textbook, will be used in the lectures and assignments of the course.
•
Academic Accommodation for Medical Illness :

If you are unable to meet a course requirement due to illness or other serious circumstances, you must provide valid medical or other supporting documentation to your Dean’s office as soon as possible and contact your instructor immediately. It is the student’s responsibility to make alternative arrangements with their instructor once the accommodation has been approved and the instructor has been informed. In the event of a missed final exam, a
“Recommendation of Special Examination” form must be obtained from the Dean’s Office immediately. For further information please see: http://www.uwo.ca/univsec/handbook/appeals/medical.pdf
A student requiring academic accommodation due to illness should use the Student Medical
Certificate when visiting an off-campus medical facility or request a Record’s Release Form
(located in the Dean’s Office) for visits to Student Health Services. The form can be found at: https://studentservices.uwo.ca/secure/medical document.pdf
•
Ethical Conduct: Please note that plagiarism is a major academic offence and will be will be penalized. See Scholastic Offence Policy in the Western Academic Calendar for details.
2