Abstract
In this work, we compare three classifiers in terms of accuracy. The first is a copula-based Bayesian classifier based on elliptical and Archimedean copulas. The remaining two are Naive Bayes and Neural Networks. Such a comparison, particularly for the recently proposed Archimedean copula-based Bayesian classifiers, hasn’t been reported in the literature. The results show that copula-based Bayesian classifiers are a viable alternative to Neural Networks in terms of accuracy while keeping the models relatively simple.
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Slechan, L., Górecki, J. (2015). On the Accuracy of Copula-Based Bayesian Classifiers: An Experimental Comparison with Neural Networks. In: Núñez, M., Nguyen, N., Camacho, D., Trawiński, B. (eds) Computational Collective Intelligence. Lecture Notes in Computer Science(), vol 9329. Springer, Cham. https://doi.org/10.1007/978-3-319-24069-5_46
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DOI: https://doi.org/10.1007/978-3-319-24069-5_46
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