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

Socpus ID

8344265284 (Scopus)

Source API URL

https://api.elsevier.com/content/abstract/scopus_id/8344265284

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