A representation coefficient-based k-nearest centroid neighbor classifier

作者：

Highlights：

• Propose RCKNCN based on both NCN and representation of neighbors.

• Differentiate the contribution of each centroid neighbor via representation.

• Design a new representation coefficient-based majority voting decision.

摘要

•Propose RCKNCN based on both NCN and representation of neighbors.•Differentiate the contribution of each centroid neighbor via representation.•Design a new representation coefficient-based majority voting decision.

论文关键词：K-nearest neighbor rule,Nearest centroid neighborhood,K-nearest centroid neighbor rule,Pattern recognition

论文评审过程：Received 23 May 2021, Revised 2 December 2021, Accepted 8 January 2022, Available online 22 January 2022, Version of Record 1 February 2022.

论文官网地址：https://doi.org/10.1016/j.eswa.2022.116529