2014 Papers
Level 5 Papers >> All Papers
COMP521A Machine Learning Algorithms

15 Points

This paper covers machine learning algorithms such as the ones implemented in the WEKA machine learning workbench, including techniques that deliver state-of-the-art predictive performance.

Pre Requisite Papers
Three 300 level Computer Science papers, including
COMP321 Practical Data Mining or
COMP316 Artificial Intelligence Techniques and Applications

Corresponding Papers
COMP421 Machine Learning Algorithms

Lecturers and Tutors

A Semester

Moodle Link
COMP521 Moodle Page

Timetable
Official Timetable Information

Workload
10 hours per week, with two hours of lectures, and (on average) 8 hours spent working on the assignments and reviewing material.

Required Reading
Witten, I.H., Frank, E., and Hall, M. (2014) Data Mining: Practical Machine Learning Tools and Techniques, 3rd Edition, Morgan Kaufman.

Computing Resources
Labs 6 and 7 in R block

Assessment Ratio
Internal assessment/final examination ratio 1:0

Grading Schedule
Each of the two assignments is worth 30% of the total marks for the course. Each of the two in-class tests is worth 20% of the total marks.

Assessment Deadlines

Attendance Policy
Slides used in class will be made available on the course web page, and we will closely follow the text book. However, there will be additional explanations given in class that you may find useful.

Academic Integrity
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Performance Impairment
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Student Concerns and Complaints
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Application for Extension
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Review of Grade
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University Regulations
Your attention is drawn to the following regulations and policies, which are published in the University Calendar:

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