[1] OPITZ D, SHAVLIK J. Generating accurate and diverse members of a neural-network ensemble [M]. Cambridge, MA:The MIT Press 1996. [2] ROSEN B E. Ensemble learning using decorrelated neural networks [J]. Connection Science 1996, 8(03). [3] Zhi-Hua Zhou, Jianxin Wu, Wei Tang. Ensembling neural networks: Many could be better than all [J]. Artificial Intelligence: An International Journal 2002, 1/2(1/2). [4] Altincay H. Decision trees using model ensemble-based nodes [J]. Pattern Recognition: The Journal of the Pattern Recognition Society 2007, 12(12). [5] Ko AHR, Sabourin R, Britto AD, Oliveira L. Pairwise fusion matrix for combining classifiers [J]. Pattern Recognition: The Journal of the Pattern Recognition Society 2007, 8(8). [6] SIRLANTZIS K, HOQUE S, FAIRHURST M C. Diversity in multiple classifier ensembles based on binary feature quantisation with application to face recognition [J]. Applied Soft Computing Journal 2008, 8(01). [7] GIACINTO G, ROLI F. Design of effective neural network ensembles for image classification purposes [J]. Image and Vision Computing 2001, 19(9-10). [8] Miin-Shen Yang, Kuo-Lung Wu. A similarity-based robust clustering method [J]. IEEE Transactions on Pattern Analysis and Machine Intelligence 2004, 4(4). [9] YU Jian, HUANG Houkuan. A new weighting fuzzy C-means algorithms [A]. St Louis Missouri 2003. [10] BLAKE C L, MERZ C J. UCI Repository of Machine Learning Database [EB/OL]. http://www.ics.uci.edu/~mlean/MLRepository.html 2008. |