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Discriminative Methods for Multi-Labeled Classification

, и . In Proceedings of the 8th Pacific-Asia Conference on Knowledge Discovery and Data Mining, стр. 22--30. Springer, (2004)

Аннотация

In this paper we present methods of enhancing existing discriminative classifiers for multi-labeled predictions. Discriminative methods like support vector machines perform very well for uni-labeled text classification tasks. Multi-labeled classification is a harder task subject to relatively less attention. In the multi-labeled setting, classes are often related to each other or part of a is-a hierarchy. We present a new technique for combining text features and features indicating relationships between classes, which can be used with any discriminative algorithm.

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CiteSeerX — Discriminative Methods for Multi-Labeled Classification

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