Abstract
Error Correcting Output Coding (ECOC) is an established technique to face a classification problem with many possible classes decomposing it into a set of two class subproblems. In this paper, we propose an ECOC system with a reject option that is performed by taking into account the confidence degree of the dichotomizers. Such a scheme makes use of a coding matrix based on Low Density Parity Check (LDPC) codes that can also be usefully employed to implement an iterative recovery strategy for the binary rejects. The experimental results have confirmed the effectiveness of the proposed approach.
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References
Dietterich, T.G., Bakiri, G.: Solving multiclass learning problems via error-correcting output codes. Journ. Artif. Intell. Research 2, 263–286 (1995)
Allwein, E.L., Schapire, R.E., Singer, Y.: Reducing multiclass to binary: A unifying approach for margin classifiers. In: Proc. 17th Intl. Conf. on Mach. Learn., pp. 9–16 (2000)
Pujol, O., Radeva, P., Vitrià, J.: Discriminant ECOC: A heuristic method for application dependent design of error correcting output codes. IEEE Trans. Patt. Anal. and Mach. Intell. 28(6), 1001–1007 (2006)
García, J., et al.: Beyond Boosting: Recursive ECOC Learning Machines. In: Roli, F., Kittler, J., Windeatt, T. (eds.) MCS 2004. LNCS, vol. 3077, pp. 62–71. Springer, Heidelberg (2004)
Chow, C.: On optimum recognition error and reject tradeoff. IEEE Trans. Inf. Theory 16, 41–46 (1970)
Karu, K., Jain, A.K.: Fingerprint Classification. Patt. Rec. 29, 389–404 (1996)
Golfarelli, M., Maio, D., Malton, D.: On the error-reject trade-off in biometric verification systems. IEEE Trans. Patt. Anal. and Mach. Intell. 19, 786–796 (1997)
Tanner, R.M.: A recursive approach to low complexity codes. IEEE Trans. Inf. Theory 27, 533–547 (1981)
Shokrollahi, A.: LDPC Codes: An Introduction (April 2003)
Richardson, T., Urbanke, R.: Modern Coding Theory. Draft (December 2006)
Gallager, R.G.: Low-Density Parity-Check Codes. MIT Press, Cambridge (1963)
Blake, C., Keogh, E., Merz, C.J.: UCI Repository of Machine Learning Databases (1998), http://www.ics.uci.edu/~mlearn/MLRepository.html
Vezhnevets, A., Vezhnevets, V.: Modest AdaBoost - Teaching AdaBoost to Generalize Better. In: Graphicon-2005, Novosibirsk Akademgorodok, Russia (2005), http://graphics.cs.msu.su/en/research/boosting/index.html
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Marrocco, C., Simeone, P., Tortorella, F. (2007). Embedding Reject Option in ECOC Through LDPC Codes. In: Haindl, M., Kittler, J., Roli, F. (eds) Multiple Classifier Systems. MCS 2007. Lecture Notes in Computer Science, vol 4472. Springer, Berlin, Heidelberg. https://doi.org/10.1007/978-3-540-72523-7_34
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DOI: https://doi.org/10.1007/978-3-540-72523-7_34
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