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ITS61504

Data Mining

EXECUTIVE SUMMARY

PURPOSE (MLO2)

The purpose of this Assignment 2 is to:

1. MLO2: Communicate findings and insights derived from data mining processes effectively to both technical and non-technical stakeholders for a given scenario.

Objectives

Implementation of Apriori Algorithm: (Must use the dataset provided in Assignment 1)

Use the Apriori Algorithm using Python to apply the association analysis technique. Document the steps taken in implementing this algorithm (screenshot Python codes when documenting the steps). You may use the conventional method (developing Python scripts by a developer) and the LLM framework with advanced libraries to perform data preprocessing/evaluation only.

Document frequent item sets and association rules

Implementation of FP Algorithm: (Must use the dataset provided in Assignment 1)

Use the FP Algorithm using Python to apply the association analysis technique. Document the steps taken in implementing this algorithm (screenshot Python codes when documenting the steps). You may use the conventional method (developing Python scripts by a developer) and the LLM framework with advanced libraries to perform data preprocessing/evaluation only.

Document frequent item sets and association rules

Summary of Observations:

Provide detail explanation from the findings to the recommendations/conclusions.

Compare both algorithms when reporting interesting patterns from the findings.

Report Writing:

Present your findings in a structured and professional manner, ensuring dlarity for both technical and non-technical audiences. Also, adherence to proper file naming. This indudes the proper submission of Python code.

Deadline: Ensure that the assignment is submitted by the due date via MyTimes.

You are required to carry out this Assignment 2 assignment individually. Generally, in this assignment, you will be analyzing the same data set provided in Assignment 1 by implementing Apriori and FP algorithms to carry out association analysis, inferring interesting patterns from the findings, and making good recommendations to achieve the set objectives.

EXECUTIVE SUMMARY (30%)

Report Outline

1. Implementation of Apriori Algorithm

2. Implementation of FP Algorithm

3. Summary of Observations

Deliverables

1. A well-structured and properly formatted academic document that contains the detailed specifications for Assignment 2.

2. Python codes (PyCharm Project File/Python Files)

*Deliverable 1 must be submitted in two formats: doc and pdf

File format: AssignmentPart2_Report_SectionNo_IDNo

*Deliverable 2 must be submitted in a zip format- file format

File format: AsignmentPart2_Codes_SectionNo_IDNo

Assignment 2 Due Date: 6/3/2026 (Friday by 12.00 am - MYT) submit via mytimes.taylors.edu.my submission link.

Important Milestones for your assignment work (Assignment 2)

% of completion work of assignment (CW)

Milestone 4 (Week 4)-CW-50%: Completion of implementing association analysis algorithms

Preparation of data set for association analysis.

Application of association analysis algorithms.

Milestone 5 (Week 5)-CW-100%: Completion of inferring interesting patterns.

Identification of frequent items sets and association rules.

Completion of inferring interesting patterns from association analysis.

Preparation for Assignment 2 report submission.

Documentation & Submission Instructions

As you prepare your assignment for submission, please adhere to the following guidelines to ensure your work is clear, well-documented, and demonstrates your coding process effectively:

1. Use the provided front page template for your assignment. It should include the full details of yourself. Make sure all information is accurate and clearly presented.

2. As for documenting Python code, accompany every segment of code with detailed comments. These should explain the function and mechanism of the code, the expected outputs, and any important considerations or potential issues that might arise.

3. The academic Honors Code applies to this assignment. Plagiarized work would not be marked.

4. All assignments are due on the dates given by the instructor on MyTimes or on a certain day of the week as specified in the lesson plan.

5. All work must be original, and if taken from any works other than yours, must be properly referenced using the APA Referencing System.

6. Before proceeding to the final submission, you must first submit your PDF document to Turnitin for a plagiarism check. Ensure you review the similarity report (similarity rate should be below 25%) and make any necessary adjustments to your work to adhere to academic integrity guidelines. Attach the one-page Turnitin report to the assignment report.

7. Submit the Assessment Submission Declaration Form along with the assignment report. (Zip this form along with the assignment report)

8. You MUST submit your assignment via MyTimes only.

9. All information, figures, and diagrams obtained from external sources must be referenced using the APA referencing system accordingly.

10. Plagiarism and collusion are serious offences, and all students involved will automatically be awarded zero marks.

11. Take note: Submission of the assignment DOES NOT mean that you pass the assignment by default. Reasons for failing to submit assignment in a timely manner due to computer crash/repair, not feeling well are not valid.

12. Final Review: Before submission, review your PDFWord document to confirm that all parts of the assignment are included and that the document is not missing any content.

13. Incomplete submission:

a. Examples of incomplete submission-failing to submit source codes, reports, Turnitin report, details are incomplete (cover page), etc.

b. The penalty for failing to submit either source code or report or both, is zero marks. and for other types of incomplete submissions, the penalty is that your assignment marks will be capped at B- (grade).

14. Failure in Compliance:

a. Examples: failing to observe similarity rate, APA referencing system, etc.

b. The penalty is that your assignment marks will be capped at B- (grade).

15. Late submission:

a. Late submission (1 to 3 days-including non-working days)-assignment marks will be capped at B-(low end-60)

b. Late submission (4 to 6 days-including non-working days)-assignment marks will be capped at C (low end-50)

c. Any late submission on the 7th day or after (including non-working days)-assignment marks will be zero