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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