Zijian Zheng, Geoffrey I. Webb, Kai Ming Ting  Home/Search
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Abstract: Techniques for constructing classifier committees including Boosting and Bagging have demonstrated great success, especially Boosting for decision tree learning. This type of technique generates several classifiers to form a committee by repeated application of a single base learning algorithm. The committee members vote to decide the final classification. Boosting and Bagging create different classifiers by modifying the distribution of the training set. Sasc (Stochastic Attribute Selection... (Update)
Context of citations to this paper: More
.... of decision trees but through different mechanisms, we developed another technique to further improve the accuracy of decision trees [14]. The new approach is called SASCB (Stochastic Attribute Selection Committees with Boosting) a combination of the Boosting and Sasc...
.... As an alternative approach to generating different classifiers to form a committee, Sasc (Stochastic Attribute Selection Committees) (Zheng and Webb 1998) builds different classifiers by modifying the set of attributes considered at each node, while the distribution of the...
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BibTeX entry: (Update)
Zheng, Z., Webb, G.I., and Ting, K.M.: Integrating Boosting and stochastic attribute selection committees for further improving the performance of decision tree learning. Proceedings of the 10th IEEE International Conference on Tools with Artificial Intelligence. IEEE Computer Society Press (1998) 216-223. http://citeseer.ist.psu.edu/article/zheng98integrating.html More
@article{ zheng98integrating,
author = "Mingchun Zheng and Jiahong Zhang and Yanbing Wang",
title = "Integrating a Formal Specification Notation with {HOOD}",
journal = "ACM SIGSOFT Software Engineering Notes",
volume = "23",
number = "5",
pages = "47--61",
year = "1998",
url = "citeseer.ist.psu.edu/article/zheng98integrating.html" }
Citations (may not include all citations):2177 Program for Machine Learning (context) - Quinlan - 1993
500 Experiments with a New Boosting Algorithm - Freund, Schapire
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243 Boosting the Margin: A New Explanation for the Effectiveness.. - Schapire, Freund et al. - 1997
183 Solving Multiclass Learning Problems via Error-correcting Ou.. - Dietterich, Bakiri - 1995
155 An Empirical Comparison of Voting Classification Algorithms:.. - Bauer, Kohavi - 1998
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17 Working Notes of AAAI Workshop on Integrating Multiple Learn.. (context) - Chan, Stolfo et al. - 1996
11 Machine Learning Bias (context) - Dietterich, Kong - 1995
9 Stochastic Attribute Selection Committees - Zheng, Webb - 1998
8 Why does Bagging Work (context) - Domingos - 1997
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