A Novel Bayesian Classifier using Copula Functions
نویسنده
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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ورودعنوان ژورنال:
- CoRR
دوره abs/cs/0611150 شماره
صفحات -
تاریخ انتشار 2006