Classification of Incomplete Data Using the Fuzzy ARTMAP Neural Network

Eric Granger; Mark A. Rubin; Stephen Grossberg; Pierre Lavoie

doi:10.1109/IJCNN.2000.859369

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Neural Networks, IEEE - INNS - ENNS International Joint Conference on

Classification of Incomplete Data Using the Fuzzy ARTMAP Neural Network

Year: 2000, Volume: 6, Pages: 6035

DOI Bookmark: 10.1109/IJCNN.2000.859369

Authors

Eric Granger, Department of National Defense and ?cole Polytechnique de Montr?al
Mark A. Rubin, Boston University
Stephen Grossberg, Boston University
Pierre Lavoie, Department of National Defense

Abstract

The fuzzy ARTMAP neural network is used to classify data that is incomplete in one or more ways. These include a limited number of training cases, missing components, missing class labels, and missing classes. Modifications for dealing with such incomplete data are introduced, and performance is assessed on an emitter identification task using a database of radar pulses.

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