Bayesian Multicategory Support Vector Machines
نویسندگان
چکیده
We show that the multi-class support vector machine (MSVM) proposed by Lee et al. (2004) can be viewed as a MAP estimation procedure under an appropriate probabilistic interpretation of the classifier. We also show that this interpretation can be extended to a hierarchical Bayesian architecture and to a fully-Bayesian inference procedure for multiclass classification based on data augmentation. We present empirical results that show that the advantages of the Bayesian formalism are obtained without a loss in classification accuracy.
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ورودعنوان ژورنال:
- CoRR
دوره abs/1206.6863 شماره
صفحات -
تاریخ انتشار 2006