Machine Learning & Data Mining | CSE 450

14 Prove : Semester Project - Final Report

Instructions

Turn in a professional report outlining the process and results of your work on your semester project.

Evaluation Criteria

As discussed at the beginning of the semester, your project will be evaluated according to the following criteria:

• Demonstrates understanding of the business needs / context of the data

• Demonstrates ability to handle non-trivial dataset

• (e.g., data set size, complexity of features, missing data, redundant attributes, obtaining the data, etc.)

• Demonstrates proper algorithm selection and application

• Discovered something interesting / of value

• (e.g., about the data, about the algorithms and their limitations in this context, something actionable for a stakeholder, etc.)

• Demonstrates understanding of limitations of the solution and potential ethical issues

• Conversant in appropriate terminology and technologies

Sections to Include

To demonstrate your achievement of these points, please prepare a final project report. Please note, this report should be in the format of a research paper document, with paragraphs, headings, full sentences, etc., not just a bulleted list of responses to these specific questions.

Please use the following sections and questions to guide you:

1. Contact information

   • (If completed in a team) Name of each team member

   • The source of the data that you analyzed

2. Introduction

   • Describe the dataset that you chose, why the problem is interesting, what you hoped to accomplish as you began, and what you actually did accomplish.

3. Data Preparation

   • Describe the process of gathering, pre-processing, and otherwise preparing the data for analysis.

   • Include examples of why this dataset was non-trivial and how you overcame these challenges.

4. Mining / learning from the data

   • Describe the process you used to mine the data, or learn patterns from it. What algorithms did you try, why did you try them? What parameters did you use and why?

   • Make sure to discuss different things you tried along the way, even if they resulted in dead ends.

   • Highlight challenges you faced and how you overcame them.

5. Results

   • Present the results that you obtained from the work done in the previous sections.

   • Include graphs and charts to support your findings. (Don't forget to include proper titles, axis labels, etc. for all graphs)

6. Conclusions (including business takeaways and action items)

   • Describe why your results could be of value to a business or stakeholder in your area. What would they know or what could they do differently as a result of your work.

   • Explain why your results constitute something "interesting."

   • Don't forget to discuss potential limitations or ethical issues.

7. Lessons Learned

   • What did you learn from this project?

   • What would you do differently if you could start this project again?

Formatting Requirements

Your reports should be professional in appearance, format, and organization. They should be free from spelling and grammar errors.

Each report should be submitted in PDF format and should be a maximum of 5 pages including images and graphs.

Submission

When complete, submit to I-Learn a PDF copy of your final report.