An online isotonic separation with cascade architecture for binary classification

作者：

Highlights：

• Cascade Isotonic separation is an online algorithm to construct model on large data.

• It provides an exact solution for the large scale LPP.

• The data chunk are divided into partitions based on dominance property and trained using cascade structure.

• Results prove that cascade-IS outperforms its counterparts in terms of model, training time and performance measures.

摘要

•Cascade Isotonic separation is an online algorithm to construct model on large data.•It provides an exact solution for the large scale LPP.•The data chunk are divided into partitions based on dominance property and trained using cascade structure.•Results prove that cascade-IS outperforms its counterparts in terms of model, training time and performance measures.

论文关键词：Isotonic separation,Cascade Isotonic separation,Cascading

论文评审过程：Received 22 March 2019, Revised 5 February 2020, Accepted 18 April 2020, Available online 24 April 2020, Version of Record 11 May 2020.

论文官网地址：https://doi.org/10.1016/j.eswa.2020.113466