Minimally-Sized Balanced Decomposition Schemes for Multi-class Classification

作者: Evgueni N. Smirnov , Matthijs Moed , Georgi Nalbantov , Ida Sprinkhuizen-Kuyper

DOI: 10.1007/978-3-642-22910-7_3

关键词:

摘要: Error-Correcting Output Coding (ECOC) is a well-known class of decomposition schemes for multi-class classification. It allows representing any multiclass classification problem as set binary problems. Due to code redundancy ECOC can significantly improve generalization performance on However, they face computational complexity when the number classes large.

参考文章(18)
Jason Weston, Chris Watkins, Support vector machines for multi-class pattern recognition. the european symposium on artificial neural networks. pp. 219- 224 ,(1999)
Pedro Domingos, A Unified Bias-Variance Decomposition for Zero-One and Squared Loss national conference on artificial intelligence. pp. 564- 569 ,(2000)
Eun Bae Kong, Thomas G. Dietterich, Error-Correcting Output Coding Corrects Bias and Variance Machine Learning Proceedings 1995. pp. 313- 321 ,(1995) , 10.1016/B978-1-55860-377-6.50046-3
Miguel Moreira, Eddy Mayoraz, On the Decomposition of Polychotomies into Dichotomies international conference on machine learning. pp. 219- 226 ,(1997)
Mark A. Hall, Ian H. Witten, Eibe Frank, Data Mining: Practical Machine Learning Tools and Techniques ,(1999)
William W. Cohen, Fast Effective Rule Induction Machine Learning Proceedings 1995. pp. 115- 123 ,(1995) , 10.1016/B978-1-55860-377-6.50023-2
T. G. Dietterich, G. Bakiri, Solving multiclass learning problems via error-correcting output codes Journal of Artificial Intelligence Research. ,vol. 2, pp. 263- 286 ,(1994) , 10.1613/JAIR.105
Yoav Freund, Robert E Schapire, A Decision-Theoretic Generalization of On-Line Learning and an Application to Boosting conference on learning theory. ,vol. 55, pp. 119- 139 ,(1997) , 10.1006/JCSS.1997.1504
Ana Carolina Lorena, André CPLF De Carvalho, João MP Gama, None, A review on the combination of binary classifiers in multiclass problems Artificial Intelligence Review. ,vol. 30, pp. 19- 37 ,(2008) , 10.1007/S10462-009-9114-9