Classification of incomplete data using the fuzzy ARTMAP neural network
Éric Granger, M.A. Rubin, Stephen Grossberg, Pierre Lavoie · 2000
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.