Machine Learning

Accurate Bayesian Data Classification without Hyperparameter Cross-validation

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  • arXiv
    5 pts

    Accurate Bayesian Data Classification without Hyperparameter Cross-validation

    We extend the standard Bayesian multivariate Gaussian generative data classifier by considering a generalization of the conjugate, normal-Wishart prior distribution and by deriving the hyperparameters analytically via evidence maximization. The behaviour of the optimal hyperparameters is explored in the high-dimensional data regime. The classification accuracy of the resulting generalized model is competitive with state-of-the art Bayesian discriminant analysis methods, but without the usual computational burden of cross-validation.

    Accurate Bayesian Data Classification without Hyperparameter Cross-validation
    by M Sheikh, A C C Coolen
    https://arxiv.org/pdf/1712.09813v1.pdf

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