A rule extraction approach from support vector machines for diagnosing hypertension among diabetics

作者：

Highlights：

• Classification of datasets on diabetes and its complications are considered.

• Five feature selection algorithms are utilized for choosing significant features.

• A hybrid rule-extraction method generating comprehensible rule sets is developed.

• Experiments were performed on six datasets: one new and five public.

• The proposed approach outperforms ten state-of-the-art classifiers.

摘要

•Classification of datasets on diabetes and its complications are considered.•Five feature selection algorithms are utilized for choosing significant features.•A hybrid rule-extraction method generating comprehensible rule sets is developed.•Experiments were performed on six datasets: one new and five public.•The proposed approach outperforms ten state-of-the-art classifiers.

论文关键词：Diabetes,Extreme gradient boosting,Hypertension,Medical diagnosis,Rule extraction,Support vector machine

论文评审过程：Received 12 June 2018, Revised 16 April 2019, Accepted 16 April 2019, Available online 17 April 2019, Version of Record 23 April 2019.

论文官网地址：https://doi.org/10.1016/j.eswa.2019.04.029