Convergence properties of a fuzzy ARTMAP network

FAMR (Fuzzy ARTMAP with Relevance factor) is a FAM (Fuzzy ARTMAP) neural network used for classification, probability estimation [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 capability, 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.

• Type: Conference
• Year: 2004
• Where: ESANN
• Authors: Razvan Andonie, Lucian Sasu
• Keywords: ESANN 2004, ESANN 2007, Fuzzy ARTMAP, Incremental Learning Capability, Relevance Factor