20 Points This paper is a practical introduction to data mining. Students will gain hands-on experience using the WEKA open-source data mining software developed by the Computer Science Department and used by companies and unversities both in New Zealand and overseas.
COMP103 Introduction to Computer Science 1 and
20 points at 200 level in Computer Science.
B Semester
http://elearn.waikato.ac.nz/
Official Timetable Information
Witten, Frank, and Hall. (2013) Data Mining: Practical Machine Learning Tools and Techniques. 3rd Ed. Morgan Kaufmann.
Slides will be available on-line at the course website.
You will have access Windows machines in Lab 5, R-block, throughout the course.
Lab work (tutorials) : 30%
Assignments: 20%
Test : 15%
Exam : 35%
Internal assessment/final examination ratio 2:1
All assessment is compulsory. An overall mark of 50% is required for a pass, with a minimum of 40% in the final exam and a minimum of 40% for coursework.
Class attendance is expected. You are responsible for all material covered in class.
Academic Integrity Follow this link for Academic Integrity information. Performance Impairment Follow this link for information on Performance Impairment. Student Concerns and Complaints Follow this link for Student Concerns and Complaints information. Application for Extension Follow this link for information on applying for an Extension.
Review of Grade Follow this link for information on applying for a Review of Grade.
University Regulations Your attention is drawn to the following regulations and policies, which are published in the University Calendar:
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