18s1: COMP9417 Machine Learning and Data Mining
Assignment 2 – Introduction
May 7, 2018
Aims
Learning objectives of this assignment:
• a self-selected task to extend aspects of the course material
• involves practical aspects of the machine learning problem, i.e.
– implementing or modifying algorithms and/or
– experimental evaluation of algorithms on data set(s)
• exercise written communication skills in motivating, recording and
summarising work done on a specified task
COMP9417: May 7, 2018 Assignment 2: Slide 1
Submission
The hand-in for this assignment has two parts:
• files containing program code to do something interesting with data
set(s) and/or results of running programs on data set(s)
– compressed archive of files
• a report on what you did.
– single document in PDF format
NOTE: there is a default 2MB limit on the size of give submissions.
If this is a problem then let me know and this can be changed or an
alternative submission method will be arranged.
COMP9417: May 7, 2018 Assignment 2: Slide 2
Marking
Total: 30 marks available (rounded up to the nearest integer)
Part 1: [12 marks]
8 marks: solving the basic problem as described in the topic
4 marks: extra features, or 1 person solving most or all of a > 1 person
problem
Part 2: [10 marks]
6 marks: describing the problem and your solution
4 marks: good presentation and communication of results
Balancing: [8 marks]
5 marks: difficulty
3 marks: achievement
COMP9417: May 7, 2018 Assignment 2: Slide 3
Marking
Why have balancing ? To take account of different levels of difficulty of
the tasks undertaken, and different levels of accomplishment of those tasks.
The difficulty assigned to each project in the spec is added to one of the
three levels of achievement judged by the overall impression obtained from
the combination of Parts 1 & 2:
difficulty achievement
5 high 3
4 good 2
3 acceptable 1
2
1
COMP9417: May 7, 2018 Assignment 2: Slide 4
Part 1
Marks will be gained by:
• evidence of good design or planning by breaking down the problem into
sub-components
• rigorous collection of results
• use of comments and notes to record decisions taken and reasons for
them in the process of the work
COMP9417: May 7, 2018 Assignment 2: Slide 5
Part 1
Marks will be lost by:
• programs failing to compile or run
• missing results files
• no clear information on contents of files submitted (e.g. in README)
• evidence of plagiarism
COMP9417: May 7, 2018 Assignment 2: Slide 6
Part 2
Marks will be gained by:
• evidence of thorough testing of an idea
• good presentation and summarisation of key results using tables, graphs,
etc.
• simple, clear and relevant explanations
• well-formatted, well-organised, spell-checked and grammar-checked
documents
COMP9417: May 7, 2018 Assignment 2: Slide 7
Part 2
Marks will be lost by:
• inappropriate length (aim for around 2 pages per group member —
extra figures, tables, etc. can go in an appendix of reasonable length)
• digression, rambling or waffling to fill space unnecessarily
• errors or inconsistencies in presentation, such as
– incorrect description of algorithms or their properties
– poor algorithm selection for a task
– errors in evaluation like not using an independent test set or cross-
validation if this is required
– statements or conclusions not based either on your experimental
results or referenced sources
– incorrect or inappropriate use of statistical tests
• evidence of plagiarism
COMP9417: May 7, 2018 Assignment 2: Slide 8
Deadline
Sunday June 3 23:59:59 (contact LiC if you need an extension)
COMP9417: May 7, 2018 Assignment 2: Slide 9