URI Data Mining and Machine Learning Group

* IMPORTANT: Room Change: Gilbreth Hall, Rm 118 *

Welcome to the URI Data Mining and Machine Learning Group. The mission of the group is to disseminate information on data mining and machine learning including, but not limited to, algorithms, methodologies, statistical foundations, and new results. We maintain an email list. If you would like to receive notifications about events or meetings regarding this group, please send an email indicating so to Dr. Lutz Hamel (hamel@cs.uri.edu ). We meet Mondays from 2-3pm in Gilbreth Hall Rm 118 on the Kingston Campus.

Upcoming Talks for the Spring 2004 semester:

Date	Name	Title of the Talk
2/2/04	Prof. Jim Kowalski	An Introduction to RBF Networks
2/9/04	Natalya Dymova	Modeling IVF Data with Support Vector Machines
2/23/04	Michael Berry	A Case Study in Data Mining
3/1/04	Illya Mowerman	Product Release Analysis with Self-Organizing Maps
3/22/04	Prof. Clare Congdon	Gaphyl: An Evolutionary Algorithms Approach for the Study of Natural Evolution
4/5/04	Chi Shen	Implementing Inductive Equational Logic
4/19/04	Dr. Susie Stephens	Oracle Life Sciences Analysis Tools
4/26/04	Natalya Dymova & Robert Burrows, PhD	Statistical Computing in R: A Tutorial

Previous Semesters:
Fall 2003
Spring 2003

Selected Projects:
Analysis of IVF Data
Inductive Equational Logic Programming
Creative Evolutionary Systems: Automatic Narrative Evolution

Background Material:
Introduction to Data Mining and Knowledge Discovery, Third Edition, Two Crows Corporation, 1999. Local copy in PDF format.
Principles of Data Mining, David J. Hand, Heikki Mannila and Padhraic Smyth, MIT Press, 2001.
Machine Learning, Tom Mitchell, McGraw-Hill, 1997.

Other Resources:
KDNuggets
ACM SIGKDD

Maintained by Lutz Hamel