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2003
Springer

On Hadamard-Type Output Coding in Multiclass Learning

8 years 8 months ago
On Hadamard-Type Output Coding in Multiclass Learning
The error-correcting output coding (ECOC) method reduces the multiclass learning problem into a series of binary classifiers. In this paper, we consider the dense ECOC methods, combining an economical number of base learners. Under the criteria of row separation and column diversity, we suggest the use of Hadamard matrices to design output codes and show them better than other codes of the same size. Comparative experiments based on the support vector machines are made for some real datasets from the UCI machine learning repository. Keywords. Multiclass learning, error-correcting output codes, Hadamard matrix, support vector machines.
Aijun Zhang, Zhi-Li Wu, Chun Hung Li, Kai-Tai Fang
Added 07 Jul 2010
Updated 07 Jul 2010
Type Conference
Year 2003
Where IDEAL
Authors Aijun Zhang, Zhi-Li Wu, Chun Hung Li, Kai-Tai Fang
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