Title
Putting The Utility Of Match Tracking In Fuzzy Artmap Training To The Test
Abstract
An integral component of Fuzzy ARTMAP's training phase is the use of Match Tracking (MT), whose functionality is to search for an appropriate category that will correctly classify a presented training pattern in case this particular pattern was originally misclassified. In this paper we explain the MT's role in detail, why it actually works and finally we put its usefulness to the test by comparing it to the simpler, faster alternative of not using MT at all during training. Finally, we present a series of experimental results that eventually raise questions about the MT's utility. More specifically, we show that in the absence of MT the resulting, trained FAM networks are of reasonable size and exhibit better generalization performance.
Publication Date
1-1-2003
Publication Title
Lecture Notes in Artificial Intelligence (Subseries of Lecture Notes in Computer Science)
Volume
2774 PART 2
Number of Pages
1-6
Document Type
Article; Proceedings Paper
Personal Identifier
scopus
DOI Link
https://doi.org/10.1007/978-3-540-45226-3_1
Copyright Status
Unknown
Socpus ID
8344265284 (Scopus)
Source API URL
https://api.elsevier.com/content/abstract/scopus_id/8344265284
STARS Citation
Anagnostopoulos, Georgios C. and Georgiopoulos, Michael, "Putting The Utility Of Match Tracking In Fuzzy Artmap Training To The Test" (2003). Scopus Export 2000s. 1978.
https://stars.library.ucf.edu/scopus2000/1978