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Recursive ECOC classification
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DOI：10.1016/j.patrec.2009.09.031.png)
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Abstract
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The construction of ECOC (Error Correcting Output Coding) classifiers from one or more constituent ECOC classifiers is proposed. Aiming to boost the accuracy of the overall ECOC system, constituent ECOC classifiers are allowed to exchange information via shared binary classifiers. A novel decoding algorithm that iteratively combines binary predictions from constituent ECOC classifiers is introduced for this purpose. Aiming to minimize the degrading effects of dependency between binary predictions, the use of sparsely connected ECOC classifiers of small size is recommended. A comprehensive experimental work shows that competitive ECOC classifiers of size at most inverted right perpendicular3 . log(2)Minverted left perpendicular can be obtained in this way. (C) 2009 Elsevier B.V. All rights reserved.
Keywords:
Multiclass classification
Output coding
ECOC
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