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890 IEEE TRANSACTIONS ON NEURAL NETWORKS, VOL. 20, NO. 5, MAY 2009 [9] H. Lin and L. Li, "Large-margin thresholded ensembles for ordinal re-
 

Summary: 890 IEEE TRANSACTIONS ON NEURAL NETWORKS, VOL. 20, NO. 5, MAY 2009
[9] H. Lin and L. Li, "Large-margin thresholded ensembles for ordinal re-
gression: Theory and practice," in Proc. 17th Int. Conf. Algorithmic
Learn. Theory, 2006, pp. 319333.
[10] S. Kramer, G. Widmer, B. Pfahringer, and M. DeGroeve, "Prediction
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[11] S. Har-Peled, D. Roth, and D. Zimak, "Constraint classification: A new
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[12] R. Herbrich, T. Graepel, and K. Obermayer, "Lrage margin rank
boundaries for ordinal regression," in Advances in Large Margin
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[13] P. McCullagh and J. A. Nelder, Generalized Linear Models. London,
U.K.: Chapman & Hall, 1983.
[14] P. McCullagh, "Regression models for ordinal data," J. Roy. Statist.
Soc. B, vol. 42, no. 2, pp. 109142, 1980.
[15] V. E. Johnson and J. H. Albert, Ordinal Data Modeling (Statistics for
Social Science and Public Policy). New York: Springer-Verlag, 1999.
[16] A. Shashua and A. Levin, "Ranking with large margin principle: Two

  

Source: Abu-Mostafa, Yaser S. - Department of Mechanical Engineering & Computer Science Department, California Institute of Technology

 

Collections: Computer Technologies and Information Sciences