Journal of the Korean Data and Information Science Society
- Volume 19 Issue 1
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- Pages.25-36
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- 2008
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- 1598-9402(pISSN)
Data-Adaptive ECOC for Multicategory Classification
- Seok, Kyung-Ha (Department of Data Science and Institute of Statistical Information, Inje University)
- Published : 2008.02.29
Abstract
Error Correcting Output Codes (ECOC) can improve generalization performance when applied to multicategory classification problem. In this study we propose a new criterion to select hyperparameters included in ECOC scheme. Instead of margins of a data we propose to use the probability of misclassification error since it makes the criterion simple. Using this we obtain an upper bound of leave-one-out error of OVA(one vs all) method. Our experiments from real and synthetic data indicate that the bound leads to good estimates of parameters.