WPI Worcester Polytechnic Institute

Computer Science Department
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CS 525D KNOWLEDGE DISCOVERY AND DATA MINING - Fall 2009  
Project 6: Anomaly Detection and Advanced Data Mining Applications

PROF. CAROLINA RUIZ 

DUE DATE: Tuesday Dec. 15, 2009. ------------------------------------------

Project Description

[200 points: 100 points the anomaly detection part and 100 points for the additional advanced data mining technique of your choice. Additional points will be given to particularly creative and/or high quality work, and/or for independently researching related techniques not covered in class.]

  • Performance Metric(s): Use performance metrics appropriate to the mining application that you chose. If you are not aware of any, propose a variety of approaches to measure how good the results of your experiments are. Consider using visualization of the constructed model or patterns to evaluate your results. The more creative/ingenious your approaches, the better. You might want to extend the Weka code to provide the evaluation/interpretation functionality you need.

  • General Comments Focus on experimenting with different ways of preprocessing the data, adapting different techniques studied in this course to tackle the problem at hand, and investigating on your own other existing approaches. The more creative/ingenious your work and/or the more research into the related literature you do, the better.