A Gaussian mixture model based discretization algorithm for associative classification of medical data

作者：

Highlights：

• A new supervised discretization algorithm is proposed.

• Multi-modal distributed numerical variables/features are particularly handled.

• The proposed approach outperforms existing algorithms in rule-based classification.

摘要

•A new supervised discretization algorithm is proposed.•Multi-modal distributed numerical variables/features are particularly handled.•The proposed approach outperforms existing algorithms in rule-based classification.

论文关键词：Discretization,Gaussian mixture model,Associative classification,Medical informatics,Clinical decision support system

论文评审过程：Received 17 July 2015, Revised 25 March 2016, Accepted 26 March 2016, Available online 8 April 2016, Version of Record 17 April 2016.

论文官网地址：https://doi.org/10.1016/j.eswa.2016.03.046