CS 539 A99 - Project 4

select an ML technique/paradigm (mutually agreed upon with the instructor ) not covered by the previous 3 projects nor by other students in the class. These techniques include, but are not limited to, instance-based learning, genetic algorithms, rule learning, and reinformen t learning;
research the ML literature on this technique;
design and implement a prototype system that solves the learning task using the chosen learning technique;
apply the constructed system to the census-income dataset;
write a webpage summarizing the relevant background knowledge and project results;
and give a 30 minute, oral, in-class presentation describing the achievements of this project.

A comparison of the results obtained by the different learning techniques/algo rithms will be drawn as a group effort.

Program. You should submit your code by email to ruiz@cs.wpi.edu.
Written Report. Please bring your report to my office (FL232) or to class by the due date/time. Your report should discuss the following issues:
1. brief overview of the choosen learning technique,
2. discussion of your literature review,
3. description of your code,
4. the experiments you ran with the system,
5. experimental results,
6. evaluation of the accuracy of the system over the training data,
7. strengths and the weaknesses of your system.
Your report should also include a short user manual explaining how to install, run, and use your system.
Oral Report. We will have 30 minute oral presentation of each of the individual projects during the class on April 13.

Janet Burge	Genetic Algorithms
Weiyang Lin	Rule-based Learning
Shawn Nicholson	Instance-based Learning
Seshubabu Pasam	Reinforcement Learning ( Report)