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Abstract:
This article presents a Support Vector Machine (SVM) like
learning system to handle multi-label problems. Such problems are
usually decomposed into many two-class problems but the
expressive power of such a system can be weak [5, 7]. We explore
a new direct approach. It is based on a large margin ranking
system that shares a lot of common properties with SVMs. We
tested it on a Yeast gene functional classification problem with
positive results.
References
[5] A. McCallum. Multi-label text classification with a
mixture model trained by EM.
AAAI'99 Workshop on Text Learning
, 1999.
[7] R. E. Schapire and Y. Singer. Boostexter: A boosting-based
system for text categorization.
Machine Learning
, 39(2/3):135-168, 2000.
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