Corpus ID: 5157458

A Novel Bayesian Classifier using Copula Functions

@article{Sathe2006ANB,
  title={A Novel Bayesian Classifier using Copula Functions},
  author={S. Sathe},
  journal={ArXiv},
  year={2006},
  volume={abs/cs/0611150}
}
  • S. Sathe
  • Published 2006
  • Mathematics, Computer Science
  • ArXiv
  • 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. 
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    References

    SHOWING 1-10 OF 17 REFERENCES
    The Estimation Method of Inference Functions for Margins for Multivariate Models
    • 588
    Parameter selection for support vector machines
    • 136
    • PDF
    Efficient tuning of SVM hyperparameters using radius/margin bound and iterative algorithms
    • S. Keerthi
    • Computer Science, Medicine
    • IEEE Trans. Neural Networks
    • 2002
    • 309
    Making large scale SVM learning practical
    • 5,364
    • PDF
    Understanding Relationships Using Copulas
    • 1,096
    • Highly Influential
    • PDF
    On the mean accuracy of statistical pattern recognizers
    • G. Hughes
    • Mathematics, Computer Science
    • IEEE Trans. Inf. Theory
    • 1968
    • 2,345
    • PDF
    1 UNDERSTANDING RELATIONSHIPS USING COPULAS *
    • 22
    • PDF
    An Introduction to Copulas
    • 6,528
    • Highly Influential
    • PDF
    The effect of unlabeled samples in reducing the small sample size problem and mitigating the Hughes phenomenon
    • 558
    • Highly Influential
    • PDF
    Analyzing high-dimensional multispectral data
    • 217
    • PDF