Interval–valued fuzzy and intuitionistic fuzzy–KNN for imbalanced data classification

作者：

Highlights：

• A resampling procedure is adapted for the imbalanced data problems.

• A suitable filter is proposed to remove the noisy and borderline samples.

• Filters apply the concepts of the interval-valued fuzzy and intuitionistic fuzzy sets.

• A new voting rule for the proposed nearest neighbor classifier (filter) is suggested.

摘要

•A resampling procedure is adapted for the imbalanced data problems.•A suitable filter is proposed to remove the noisy and borderline samples.•Filters apply the concepts of the interval-valued fuzzy and intuitionistic fuzzy sets.•A new voting rule for the proposed nearest neighbor classifier (filter) is suggested.

论文关键词：Iterative partition filtering,Interval-valued fuzzy k nearest neighbor,Interval-valued intuitionistic fuzzy sets,Imbalanced classification

论文评审过程：Received 26 April 2020, Revised 14 September 2020, Accepted 27 June 2021, Available online 5 July 2021, Version of Record 12 July 2021.

论文官网地址：https://doi.org/10.1016/j.eswa.2021.115510