IRAHC: Instance Reduction Algorithm using Hyperrectangle Clustering

作者：

Highlights：

• An instance reduction method has been proposed by using hyperrectangle clustering.

• The performance of the proposed method has been examined on real data sets.

• The results have been compared to seven important instance reduction algorithms.

• The proposed method yields the lowest classification error rate significantly.

• The proposed method has the best instance reduction percentage significantly.

摘要

•An instance reduction method has been proposed by using hyperrectangle clustering.•The performance of the proposed method has been examined on real data sets.•The results have been compared to seven important instance reduction algorithms.•The proposed method yields the lowest classification error rate significantly.•The proposed method has the best instance reduction percentage significantly.

论文关键词：Instance reduction,Instance selection,Hyperrectangle,Instance-based classifiers,k-Nearest neighbor (k-NN)

论文评审过程：Received 23 January 2013, Revised 28 July 2014, Accepted 8 November 2014, Available online 18 November 2014.

论文官网地址：https://doi.org/10.1016/j.patcog.2014.11.005