DynamicWEB_AdaptingToDrift.pdf (239.93 kB)
DynamicWEB: Adapting to concept drift in COBWEB
conference contributionposted on 2023-05-26, 09:30 authored by Joel ScanlanJoel Scanlan, Hartnett, J, Williams, R
Examining concepts that change over time has been an active area of research within data mining. This paper presents a new method that functions in contexts where concept drift is present, while also allowing for modification of the instances themselves as they change over time. This method is well suited to domains where subjects of interest are sampled multiple times, and where they may migrate from one resultant concept to another. The method presented here is an extensive modification to the conceptual clustering algorithm COBWEB, and is titled DynamicWEB.
Event title21st Australasian Joint Conference on Artifical Intelligence A1-08
Event VenueAuckland, New Zealand
Date of Event (Start Date)2008-12-03
Date of Event (End Date)2008-12-05