Root-quatric mixture of experts for complex classification problems
作者：
Highlights：
• We design a new ensemble system based on mixture of experts.
• The anti-correlation measure is augmented to error function of mixture of experts.
• The gating network assigns the weights to all of the output neurons of the experts.
• The effect of anti-correlation measure is investigated.
• Increasing anti-correlation measure will increase the diversity among the experts.
摘要
•We design a new ensemble system based on mixture of experts.•The anti-correlation measure is augmented to error function of mixture of experts.•The gating network assigns the weights to all of the output neurons of the experts.•The effect of anti-correlation measure is investigated.•Increasing anti-correlation measure will increase the diversity among the experts.
论文关键词：ME,Negative correlation learning,Neural network ensemble,Ensemble learning,Diversity,Root–quartic negative correlation learning
论文评审过程：Received 18 November 2014, Revised 19 January 2016, Accepted 20 January 2016, Available online 29 January 2016, Version of Record 15 February 2016.
论文官网地址：https://doi.org/10.1016/j.eswa.2016.01.040
