Publications
Authors:
  • Jimi Shanahan , James Baldwin , Trevor Martin
Citation:
The proceedings of the Intn'l conference of the North American Fuzzy Information Processing Society, NAFIPS 1999, New York, pp 228-232
Abstract:
Current approaches to knowledge discovery can be differentiated based on the discovered models using the
following criteria: effectiveness, understandability (to a user or expert in the domain) and evolvability (ability to
adapt over time to a changing environment). Most current approaches satisfy understandability or effectiveness,
but not simultaneously, while tending to ignore knowledge evolution. Here we show how knowledge
representation based upon Cartesian granule features and a corresponding induction algorithm can effectively
address these knowledge discovery criteria (in this paper the discussion is limited to understandability and
effectiveness) across a wide variety of problem domains including control, image understanding and medical
diagnosis.
Year:
1999
Report number:
1999/204
Attachments: