WPI Worcester Polytechnic Institute

Computer Science Department

CS525D Knowledge Discovery and Data Mining - Fall 2009 
Project Guidelines



Guidelines for Projects and for Written Reports

Each of the projects in this course deals with one or more specific machine learning techniques. The guidelines below are intended to help you structure the experimental work you are expected to do for each project, as well as your written and oral reports.

An important aspect of both your written and oral reports is the "story-telling" aspect. Try to tell the story of what experiments you ran and why, how each experiment shed lights on what experiment(s) to run next, and what you learned with them.

Experiments' Guidelines

Guidelines for Oral Reports and Slides

We will discuss the results of each project in class. Your oral report should summarize the most important parts of your written report and should elaborate only on the most significant or more unique parts of your work. Each student will have 6 minutes to present their project in class. Given the time constraint, your presentation should consist of 3-4 slides (and no more!). Try to summarize results using tables when appropriate. Be prepared and use your presentation time wisely!

Submission and Due Dates

  1. Please submit the following file containing your oral presentation by email to the professor AT LEAST ONE HOUR BEFORE THE BEGINNING OF CLASS the day the project is due:
    • [your-lastname]_projn_slides.[ext]
    containing your slides for your oral report. n is the project number. This file should be either a PDF file (ext=pdf) or a PowerPoint file (ext=ppt). Please use only lower case letters in the name file. For instance, the file with my slides for Project 1 would be named ruiz_proj1_slides.ppt

  2. Please submit a hardcopy of your written report by the beginning of class the day that the project is due.

Grading Criteria

The project grade will be distributed as follows: A detailed distribution of the total points appears in the project description above. Extra points will be given to exceptional high quality work.