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Boosting及其在数据挖掘中的应用 被引量：1

Boosting and its application in data mining
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摘要 　在介绍、分析Boosting和组合学习的基础上,讨论其在数据挖掘中的应用和可能发展的方向. This paper introduces and analyzes boosting and ensemble of learning methods. As the same time, its application and possible developing directions in data mining have been discussed.
作者 王新 沈峥
机构地区 云南民族大学数学与计算机科学学院 昆明市生物技术工程研究中心
出处 《云南民族大学学报（自然科学版）》 CAS 2004年第2期91-94,共4页 Journal of Yunnan Minzu University:Natural Sciences Edition
关键词 组合学习方法 数据挖掘 BOOSTING 分类预测 boosting ensemble of learning methods data mining
分类号 TP311.13 [自动化与计算机技术—计算机软件与理论]
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参考文献10

  • 1SCHAPIRE R E. The strength of weak leamability[J]. Machine Learning, 1990,5(2) : 197 - 227.
  • 2FREUND Y. Boosting a weak learning algorithm by majority[J] .Information and computation, 1995,121 (2) :256- 285.
  • 3FREUND Y, SCHAPIRE R E. A decision- theoretic generalization of online learning and an application to boosting[ J]. Journal of Computer and System Science, 1997,55(1):119- 139.
  • 4FREUND Y,SCHAPIRE R E. Experiments with a new boosting algorithm In Saitta, l.(Ed. )[C]. Proceedings of the Thirteenth International Conference on Machine Learning, 1996:148- 156.
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  • 9FREUND Y,SCHAPIRE R E. Experiments with a new boosting algorithm In Saitta, l.(Ed.)[C]. Proceedings of the Thirteenth International Conference on Machine Learning,1996:148-156.
  • 10FREUND Y, LYER R, SCHAPIRE R E,et al,. An efficient boosting algorithm for combining preferences in machine learning[C]. Proceedings of the Fifteenth International Conference,1998.1-9.

同被引文献16

  • 1冯夏庭.地下峒室岩爆预报的自适应模式识别方法[J].东北大学学报（自然科学版）,1994,15(5):471-475. 被引量：33
  • 2BOARD M, FAIRHURST C. Rockbursts: Prediction and Control [M]. London: The Institution of Mining and Metallurgy, 1983: 81-90.
  • 3http://cnki.whlib.ac.cn.
  • 4BREMAN L. Bagging predictors [J]. Machine Learning, 1996, 26 (2): 123- 140.
  • 5FREUND Y, SCHAPIRE R E. A short introduction to boosting [J]. Journal of Japanese Society for Artificial Intelligence, 1999, 14 (5): 771 -780.
  • 6FREUND Y, IYER R, SCHAPIRE R E. et al. An Efficient Boosting Algorithm for Combining Preferences [J]. Journal of Machine Learning Research, 2003, (4): 933 -969.
  • 7http://www.boosting.org.
  • 8SCHWENK H, BENGIO Y. Boosting Neural networks [J]. Neural Computation, 2000, 12 (8): 1 869- 1 887.
  • 9MAGHOOLI K, MOIN M S. A new approach on multimodal biometrics based on combining neural networks using adaboost [J]. European Conference on Computer Vision, 2004:332-341.
  • 10王元汉,李卧东,李启光,徐钺,谭国焕.岩爆预测的模糊数学综合评判方法[J].岩石力学与工程学报,1998,17(5):493-501. 被引量：319

引证文献1

二级引证文献42

云南民族大学学报（自然科学版）
2004年 第2期

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