A Novel Bayesian Classifier using Copula Functions
Machine Learning
2007-05-23 v3 Artificial Intelligence
Information Retrieval
Abstract
A useful method for representing Bayesian classifiers is through \emph{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.
Keywords
Cite
@article{arxiv.cs/0611150,
title = {A Novel Bayesian Classifier using Copula Functions},
author = {Saket Sathe},
journal= {arXiv preprint arXiv:cs/0611150},
year = {2007}
}