標題: MTSbag: A Method to Solve Class Imbalance Problems
作者: Hsiao, Yu-Hsiang
Su, Chao-Ton
Fu, Pin-Cheng
Chen, Mu-Chen
運輸與物流管理系 註:原交通所+運管所
Department of Transportation and Logistics Management
關鍵字: Mahalanobis-Taguchi System (MTS);Class imbalance problem;Ensemble learning;Bagging;Classification
公開日期: 1-一月-2018
摘要: Class imbalance is a common problem in classification problems. The Mahalanobis-Taguchi System (MTS) has been shown to be robust in addressing class imbalance problems owing to its inherent properties of classification model construction. The bagging learning approach often has been applied as a superior strategy to reduce the learning bias of classification algorithms. In this study, we propose MTSbag, which integrates the MTS and the bagging-based ensemble learning approaches to enhance the ability of conventional MTS in handling imbalanced data. We perform numerical experiments involving multiple datasets with various class imbalance levels to demonstrate the effectiveness of MTSbag, especially for datasets with high imbalance levels.
URI: http://dx.doi.org/10.1109/IIAI-AAI.2018.00113
http://hdl.handle.net/11536/153302
ISBN: 978-1-5386-7447-5
DOI: 10.1109/IIAI-AAI.2018.00113
期刊: 2018 7TH INTERNATIONAL CONGRESS ON ADVANCED APPLIED INFORMATICS (IIAI-AAI 2018)
起始頁: 524
結束頁: 529
顯示於類別:會議論文