Exemplar-based pattern recognition via semi-supervised learning
作者： G.C. Anagnostopoulos , M. Bharadwaj , M. Georgiopoulos , S.J. Verzi , G.L. Heileman
DOI: 10.1109/IJCNN.2003.1224008
关键词:
摘要: The focus of this paper is semi-supervised learning in the context pattern recognition. Semi-supervised (SSL) refers to construction clusters during training phase exemplar-based classifiers. Using artificially generated data sets we present experimental results classifiers that follow SSL paradigm and show that, especially for difficult recognition problems featuring high class overlap, implementing i) generalization performance improves, while ii) number necessary exemplars decreases significantly, when compared original versions
sci-hub.se 参考文章(11)
Michael Georgiopoulos, Georgios Christos Anagnostopoulos, Novel approaches in adaptive resonance theory for machine learning University of Central Florida. ,(2001)
Stephen Grossberg, Adaptive pattern classification and universal recoding: II. Feedback, expectation, olfaction, illusions Biological Cybernetics. ,vol. 23, pp. 187- 202 ,(1976) , 10.1007/BF00340335
S.J. Verzi, G.L. Heileman, M. Georgiopoulus, M.J. Healy, Rademacher penalization applied to fuzzy ARTMAP and boosted ARTMAP international joint conference on neural network. ,vol. 2, pp. 1191- 1196 ,(2001) , 10.1109/IJCNN.2001.939530
Mohamad H. Hassoun, Nathan Intrator, Susan McKay, Wolfgang Christian, Fundamentals of Artificial Neural Networks Computers in Physics. ,vol. 10, pp. 137- 137 ,(1996) , 10.1063/1.4822376
Georgios C. Anagnostopoulos, Michael Georgiopoulos, Ellipsoid ART and ARTMAP for incremental unsupervised and supervised learning Applications and Science of Computational Intelligence IV. ,vol. 4390, pp. 293- 304 ,(2001) , 10.1117/12.421180
M. Stone, Cross-Validatory Choice and Assessment of Statistical Predictions Journal of the Royal Statistical Society: Series B (Methodological). ,vol. 36, pp. 111- 133 ,(1974) , 10.1111/J.2517-6161.1974.TB00994.X
M.H. Hassoun, Fundamentals of artificial neural networks ,(1995)
G.C. Anagnostopoulos, M. Georgiopoulos, S.J. Verzi, G.L. Heileman, Reducing generalization error and category proliferation in ellipsoid ARTMAP via tunable misclassification error tolerance: boosted ellipsoid ARTMAP international joint conference on neural network. ,vol. 3, pp. 2650- 2655 ,(2002) , 10.1109/IJCNN.2002.1007562
Vladimir Naumovich Vapnik, Vlamimir Vapnik, Statistical learning theory John Wiley & Sons. ,(1998)
Vladimir N. Vapnik, The Nature of Statistical Learning Theory ,(1995)