ODOC-ELM: Optimal decision outputs compensation-based extreme learning machine for classifying imbalanced data
作者：
Highlights：
• The reason of the damage caused by class imbalance for ELM is analyzed in theory.
• The influence factors about the performance of ELM on skewed data are investigated.
• An optimal decision outputs compensation-based ELM called ODOC-ELM is presented.
• Exploring prior data distributions helps improve quality of ELM.
• Statistical results indicate the superiority of the proposed ODOC-ELM algorithm.
摘要
•The reason of the damage caused by class imbalance for ELM is analyzed in theory.•The influence factors about the performance of ELM on skewed data are investigated.•An optimal decision outputs compensation-based ELM called ODOC-ELM is presented.•Exploring prior data distributions helps improve quality of ELM.•Statistical results indicate the superiority of the proposed ODOC-ELM algorithm.
论文关键词：Extreme learning machine,Class imbalance learning,Decision outputs compensation,Prior data distributions,Optimization
论文评审过程：Received 7 April 2015, Revised 6 October 2015, Accepted 8 October 2015, Available online 26 October 2015, Version of Record 11 December 2015.
论文官网地址：https://doi.org/10.1016/j.knosys.2015.10.012
