This project is designed to provide students a good opportunity to use data mining and machine learning method in discovering knowledge from given data sets and explore the applications for business intelligence.
Students are permitted to do this project in a group of no more than 3 students. Students can also do this project individually if you choose to do so. In whichever case, it does not affect the marking criteria.
You must submit your completed project in the Dropbox in CloudDeakin and submission must follow the following requirements:
1. Each group should submit one and only one copy. Multiple submission will be penalized. 2. Your submission should be in a plain word or pdf file. 3. All submission must be via assignment dropbox. Email submission will be removed without marking. 4. The due date is on Friday, submission during the weekend is acceptable without penalty provided that the submission must be made before 9.30am of the following Monday. No further extension will be granted. 5. Late submissions (after 9.30am, of the following Monday of the due date) will be penalised. Further, the CloudDeakin server is the ultimate time keeper when it comes to determining whether your submission has been received on time. 6. The contents of the submission should include: (1) A Project cover page which should include a. Unit ID and Unit name; b. Project number; c. All group members’ ID, given name and family name; d. Group member’s contribution, such as, all member made equal contribution to the project, or A: 60%; B: 40% etc. e. Name and contact details of the group leader including phone and email. (2) The assignment declaration page (3) Main Body PART 1: PART 2: (4) Any acknowledgement and reference you may have.
7. You are also reminded to keep a backup copy for record.
What you need to do for this assignment are as follows:
[Task Specification]: There are two tasks:
PART 1. Discovery of Knowledge from given data set manually
PART 2. Discovery of Knowledge from given data set automatically And discuss its Application for Business Intelligence
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