Clustered Bayesian classification for within-class separation

作者：

Highlights：

• Naïve and non-naïve Bayesian classifiers are popularly used in various areas.

• Different density estimation methods are used for continuous attributes.

• Popular density estimators do not fit to the attributes which have multiple modes.

• Proposed clustering approach proved useful in different Bayesian classifiers.

摘要

•Naïve and non-naïve Bayesian classifiers are popularly used in various areas.•Different density estimation methods are used for continuous attributes.•Popular density estimators do not fit to the attributes which have multiple modes.•Proposed clustering approach proved useful in different Bayesian classifiers.

论文关键词：Bayesian Classification,Density estimation,Clustering

论文评审过程：Received 21 October 2020, Revised 3 July 2022, Accepted 11 July 2022, Available online 16 July 2022, Version of Record 20 July 2022.

论文官网地址：https://doi.org/10.1016/j.eswa.2022.118152