Welcome to the URI Data Mining Group. The mission of the group
is to disseminate information on data mining 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 hamel@cs.uri.edu. Currently
we are meeting every Monday from 2-3pm in Tyler Hall, Room 126.
Upcoming Talks for the Spring 2003 semester:
[2/20] Dr. Paul Mangiameli -- Diagnosing Breast Cancer with Ensemble
Strategies for a Medical Diagnostic Decision Support System
Talk
will be held in INDEP 210, 3:30-4:45 (paper,
powerpoint slides)
[2/24] Dr. Lutz Hamel -- Data Mining with Decision Trees (powerpoint
slides)
[3/3] Dr. Lutz Hamel -- Data Mining beyond Decision Trees (html
presentation slides)
[3/24] Julie Goodside -- The "Insightful Miner" Data Mining Tool
[3/31] Tim Ren -- Optimization of artificial neural networks in
satellite remote sensing data analysis (powerpoint
slides)
[4/7] Eric Kyper -- Neural Networks vs. Mars vs. Regression: A Comparison
(thesis,
powerpoint
slides)
[4/14] Dr. Liliana Gonzalez -- Compute Intensive Statistics
[4/21] Venkat Surapaneni -- Exploratory Data Analysis for Data Mining
(powerpoint
slides)
[4/28] Peg Pelletier -- Bayesian Statistics and Data Analysis (powerpoint
slides)
[5/5] No Presentation
Projects:
Analysis of IVF Data
A Web-based Exploratory Data Analysis Tool
A High-Performance Data Mining Framework
in MySQL
Inductive Equational Logic Programming
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