文章基本信息
- 标题:Learning from Imbalanced Data Sets with Boosting and Data Generation: The Databoost-IM Approach
- 作者:Hongyu Guo, Herna L. Viktor
- 期刊名称:SIGKDD Explorations
- 印刷版ISSN:1931-0145
- 出版年度:2004
- 卷号:6
- 期号:1
- 页码:30-30
- 出版社:Association for Computing Machinery
- 关键词:boosting; data mining; ensembles of classifiers; imbalanced data sets
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