A hybrid neural network system for pattern classification tasks with missing features

A hybrid neural network comprising fuzzy ARTMAP and fuzzy c-means clustering is proposed for pattern classification with incomplete training and test data. Two benchmark problems and a real medical pattern classification tasks are employed to evaluate the effectiveness of the hybrid network. The results are analyzed and compared with those from other methods.