Beyond majority: Label ranking ensembles based on voting rules

作者：

Highlights：

• Aggregation methods for label ranking ensembles based on voting rules are proposed.

• It is demonstrated how different voting rules excel in different settings.

• A learning framework that selects the best voting rule for each dataset is proposed.

摘要

•Aggregation methods for label ranking ensembles based on voting rules are proposed.•It is demonstrated how different voting rules excel in different settings.•A learning framework that selects the best voting rule for each dataset is proposed.

论文关键词：Label ranking,Ensembles,Voting rules,Machine learning,Social choice

论文评审过程：Received 5 December 2018, Revised 5 June 2019, Accepted 11 June 2019, Available online 15 June 2019, Version of Record 21 June 2019.

论文官网地址：https://doi.org/10.1016/j.eswa.2019.06.022