计算机与现代化Issue(3)：83-88,6.DOI:10.3969/j.issn.1006-2475.2018.03.016
改进Smote算法在不平衡数据集上的分类研究
Research on Classification of Improved Smote Algorithm on Imbalanced Datasets
摘要
Abstract
In imbalanced datasets,the oversampling algorithm,such as Smote(Synthetic Minority Oversampling)algorithm,R-Smote algorithm and SD-ISmote algorithm, may blur the boundary between the majority and the minority and use noisy data to synthesize new samples.The ImprovedSmote algorithm proposed in this paper uses cluster center of minority set and their corre -sponding minority set to generate new samples.The Smote,the R-Smote,the SD-ISmote and the ImprovedSmote algorithm com-bined C4.5 decision tree and neural network algorithm are used on the experimental datasets.The results show that the Improv-edSmote algorithm is better than other algorithms in classification and can effectively improve classifier performance.关键词
不平衡数据集/Smote算法/R-Smote算法/SD-ISmote算法/ImprovedSmote算法/簇心Key words
imbalanced dataset/Smote/R-Smote/SD-ISmote/ImprovedSmote/cluster center分类
信息技术与安全科学引用本文复制引用
易未,毛力,孙俊,吴林海..改进Smote算法在不平衡数据集上的分类研究[J].计算机与现代化,2018,(3):83-88,6.基金项目
国家粮食公益性行业科研专项项目(201513004-6) （201513004-6）
"十二五"农村领域国家科技计划子课题(2015BAD17B02-8) （2015BAD17B02-8）
现代农业产业技术体系专项资金项目(CARS-49) （CARS-49）
江苏省产学研合作项目(BY2015019-30) （BY2015019-30）
