Bagging of credal decision trees for imprecise classification
作者：
Highlights：
• The paper presents a new method for imprecise classification.
• The method uses bagging scheme with a new proposal for combining imprecise classifications.
• To combine imprecise classifications a newfangled procedure is used.
• The new method for imprecise classification outperforms the results of a single classifier.
• An experimental study justifies the new method with excellents results.
摘要
•The paper presents a new method for imprecise classification.•The method uses bagging scheme with a new proposal for combining imprecise classifications.•To combine imprecise classifications a newfangled procedure is used.•The new method for imprecise classification outperforms the results of a single classifier.•An experimental study justifies the new method with excellents results.
论文关键词：Imprecise classification,Credal decision trees,Ensembles,Bagging,Combination technique
论文评审过程：Received 8 April 2019, Revised 28 June 2019, Accepted 7 September 2019, Available online 12 September 2019, Version of Record 19 September 2019.
论文官网地址：https://doi.org/10.1016/j.eswa.2019.112944
