A Novel Bayesian Classifier using Copula Functions

نویسنده

  • Saket Sathe
چکیده

A useful method for representing Bayesian classifiers is through discriminant functions. Here, using copula functions, we propose a new model for discriminants. This model provides a rich and generalized class of decision boundaries. These decision boundaries significantly boost the classification accuracy especially for high dimensional feature spaces. We strengthen our analysis through simulation results.

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عنوان ژورنال:
  • CoRR

دوره abs/cs/0611150  شماره 

صفحات  -

تاریخ انتشار 2006