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Annals of Data Science

Improving Bayesian Classifier Using Vine Copula and Fuzzy Clustering Technique

  • 10-08-2023
Published in:
Authors
Ha Che-Ngoc
Thao Nguyen-Trang
Hieu Huynh-Van
Tai Vo-Van
Published in
Annals of Data Science | Issue 2/2024

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Abstract

The article introduces an enhanced Bayesian classifier that leverages Vine Copula to model dependencies among variables and fuzzy clustering to determine adaptive prior probabilities. This approach overcomes the limitations of traditional Bayesian methods, which often assume independence among variables and fixed prior probabilities. The proposed method is validated through numerical examples and real-world applications, showcasing its superior performance in various domains, including healthcare and finance. The article also highlights the practical advantages of the method, such as its stability and reduced dependence on parameter tuning, making it a valuable tool for data scientists and machine learning engineers.
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Title
Improving Bayesian Classifier Using Vine Copula and Fuzzy Clustering Technique
Authors
Ha Che-Ngoc
Thao Nguyen-Trang
Hieu Huynh-Van
Tai Vo-Van
Publication date
10-08-2023
Publisher
Springer Berlin Heidelberg
Published in
Annals of Data Science / Issue 2/2024
Print ISSN: 2198-5804
Electronic ISSN: 2198-5812
DOI
https://doi.org/10.1007/s40745-023-00490-4
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