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Proceedings paper #79090

Rousu, J; Saunders, C; Szedmak, S; Shawe-Taylor, J; (2004) UNSPECIFIED In: (Proceedings) On Maximum Margin Hierarchical Classification.

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Abstract

We present work in progress towards maximum margin hierarchical classification where the objects are allowed to belong to more than one category at a time. The classification hierarchy is represented as a Markov network equipped with an exponential family defined on the edges. We present a variation of the maximum margin multilabel learning framework, suited to the hierarchical classification task and allows efficient implementation via gradient-based methods. We compare the behaviour of the proposed method to the recently introduced hierarchical regularized least squares classifier as well as two SVM variants in Reuter's news article classification

Type:Proceedings paper
Event:On Maximum Margin Hierarchical Classification
Keywords:SVM
UCL classification:UCL > School of BEAMS > Faculty of Engineering Science > Computer Science

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