Abstract
Friedman(1996) proposed a strategy for the classification multigroup problem. He build independently a classifier for each pair of classes and then combined all the pairwise decisions to form the final decision. We suggest an alternate approach in the context of EDDA models. Our technique, the hierarchical coupling, is also based on pairwise decisions but we abandon the independence and work on nested pairs of classes. We evaluate the performance of hierarchical coupling on simulated and real datasets.
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References
BENSMAIL, H. and CELEUX, G. (1996): Regularized Gaussian Discriminant Analysis through Eigenvalue decomposition. Journal of the American Statistical Association, 91, 1743–48.
FRIEDMAN, J. (1996): Another approach to polychotomous classification. Technical Report. Stanford University.
HASTIE, T. and TIBSHIRANI, R. (1996): Classification by pairwise coupling. Technical Report. University of Toronto.
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© 2000 Springer-Verlag Berlin · Heidelberg
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Brito, I., Celeux, G. (2000). Discriminant Analysis by Hierarchical Coupling in EDDA Context. In: Kiers, H.A.L., Rasson, JP., Groenen, P.J.F., Schader, M. (eds) Data Analysis, Classification, and Related Methods. Studies in Classification, Data Analysis, and Knowledge Organization. Springer, Berlin, Heidelberg. https://doi.org/10.1007/978-3-642-59789-3_28
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DOI: https://doi.org/10.1007/978-3-642-59789-3_28
Publisher Name: Springer, Berlin, Heidelberg
Print ISBN: 978-3-540-67521-1
Online ISBN: 978-3-642-59789-3
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