A novel dependency-oriented mixed-attribute data classification method

作者：

Highlights：

• Dependency-Oriented aggregation of RVFL network and NBC was proposed.

• The new feature dependence and independence exploration strategies were designed.

• The exhaustive experiments were conducted to validate the effectiveness of new model.

• The reasons why model can obtain the better prediction performances were revealed.

摘要

•Dependency-Oriented aggregation of RVFL network and NBC was proposed.•The new feature dependence and independence exploration strategies were designed.•The exhaustive experiments were conducted to validate the effectiveness of new model.•The reasons why model can obtain the better prediction performances were revealed.

论文关键词：Mixed-attribute data classification,Attribute independence,Random vector functional link network,Naive Bayes classifier,One-hot encoding,Attribute discretization

论文评审过程：Received 6 September 2021, Revised 27 December 2021, Accepted 26 February 2022, Available online 17 March 2022, Version of Record 26 March 2022.

论文官网地址：https://doi.org/10.1016/j.eswa.2022.116782