Classification of Incomplete Data Using the Fuzzy ARTMAP Neural Network

Author(s): Granger, E | Grossberg, S. | Lavoie, P. | Rubin, M.A. |

Year: 2000

Citation: Proceedings of the IEEE-INNS-ENNS International Joint Conference on Neural Networks (IJCNN 2000)

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 data base of radar pulses.

Topics: Machine Learning, Applications: Other, Models: Fuzzy ARTMAP,

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