A novel and powerful hybrid classifier method: Development and testing of heuristic k-nn algorithm with fuzzy distance metric

作者：

Highlights：

• A Novel and Powerful Hybrid Classifier Method has been developed.

• A novel weight-tuning method is introduced by applying ABC-based heuristic searching approach.

• A powerful similarity measurement method has been introduced.

• Experimental results show that the proposed hybrid algorithms significantly improves classification results of the well-known instance-based intuitive and heuristic classification algorithms over real datasets

摘要

•A Novel and Powerful Hybrid Classifier Method has been developed.•A novel weight-tuning method is introduced by applying ABC-based heuristic searching approach.•A powerful similarity measurement method has been introduced.•Experimental results show that the proposed hybrid algorithms significantly improves classification results of the well-known instance-based intuitive and heuristic classification algorithms over real datasets

论文关键词：Classification,Data mining methods and algorithms,Artificial bee colony optimization,Fuzzy distance metric,Heuristic weight-tuning method,Hybrid k-nearest neighbor classifier

论文评审过程：Received 23 August 2012, Revised 13 February 2016, Accepted 17 February 2016, Available online 2 March 2016, Version of Record 16 May 2016.

论文官网地址：https://doi.org/10.1016/j.datak.2016.02.002