Issue No. 04 - April (2005 vol. 27)
DOI Bookmark: http://doi.ieeecomputersociety.org/10.1109/TPAMI.2005.64
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 task are employed to evaluate the effectiveness of the hybrid network. The results are analyzed and compared with those from other methods.
Missing data, Fuzzy ARTMAP, Fuzzy c-Means Clustering, pattern classification.
M. Kuan, J. Leong and C. Lim, "A Hybrid Neural Network System for Pattern Classification Tasks with Missing Features," in IEEE Transactions on Pattern Analysis & Machine Intelligence, vol. 27, no. , pp. 648-653, 2005.