Advanced Search

Browse by Discipline

Scientific Societies

E-print Alerts

Add E-prints

E-print Network

  Advanced Search  

Convergence properties of a fuzzy ARTMAP Razvan Andonie 1

Summary: Convergence properties of a fuzzy ARTMAP
Razvan Andonie 1
and Lucian Sasu 2
Computer Science Department, Central Washington University, USA
Computer Science Department, Transylvania University of Bra¸sov, Romania
Abstract. FAMR (Fuzzy ARTMAP with Relevance factor) is a FAM
(Fuzzy ARTMAP) neural network used for classification, probability es-
timation [3], [2], and function approximation [4]. FAMR uses a relevance
factor assigned to each sample pair, proportional to the importance of
that pair during the learning phase. Due to its incremental learning capa-
bility, FAMR can efficiently process large data sets and is an appropriate
tool for data mining applications. We present new theoretical results
characterizing the stochastic convergence of FAMR.
1 Introduction
An incremental learning algorithm can be defined by the following characteris-
tics [12]: i) it is able to learn additional information from new data; ii) it does
not require access to the original data, used to train the existing system; iii)


Source: Andonie, Razvan - Department of Computer Science, Central Washington University


Collections: Computer Technologies and Information Sciences