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An ensemble based approach for dealing with missing data, without predictingor imputing the missing values is proposed. This technique is suitable foronline operations of neural networks and as a result, is used for onlinecondition monitoring. The proposed technique is tested in both classificationand regression problems. An ensemble of Fuzzy-ARTMAPs is used forclassification whereas an ensemble of multi-layer perceptrons is used for theregression problem. Results obtained using this ensemble-based technique arecompared to those obtained using a combination of auto-associative neuralnetworks and genetic algorithms and findings show that this method can performup to 9% better in regression problems. Another advantage of the proposedtechnique is that it eliminates the need for finding the best estimate of thedata, and hence, saves time.

Fuzzy Artmap and Neural Network Approach to Online Processing of Inputs with Missing Values