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Abstract: Parameter tuning through cross-validation becomes very difficult when the validation set contains no or only a few examples of the classes in the evaluation set. We address this open challenge by using a combination of classifiers with different performance characteristics to effectively reduce the performance variance on average of the overall system across all classes, including those not seen before. This approach allows us to tune the combination system on available but... (Update)
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BibTeX entry: (Update)
Yang, Y., Ault, T., & Pierce, T. (2000). Combining multiple learning strategies for effective cross validation. http://citeseer.ist.psu.edu/article/yang00combining.html More
@inproceedings{ yang00combining,
author = "Yiming Yang and Thomas Ault and Thomas Pierce",
title = "Combining multiple learning strategies for effective cross-validation",
booktitle = "Proceedings of {ICML}-00, 17th International Conference on Machine Learning",
publisher = "Morgan Kaufmann Publishers, San Francisco, US",
address = "Stanford, US",
editor = "Pat Langley",
pages = "1167--1182",
year = "2000",
url = "citeseer.ist.psu.edu/article/yang00combining.html" }
Citations (may not include all citations):166 A re-examination of text categorization methods - Yang, Liu - 1999
116 Topic detection and tracking pilot study: Final report - Allan, Carbonell et al. - 1998
110 Context-sensitive learning methods for text categorization - Cohen, Singer - 1996
110 Training algorithms for linear text classifiers - Lewis, Schapire et al. - 1996
79 A post-processing system to yield reduced word error rates: .. - Fiscus - 1997
64 Nearest Neighbor (context) - Dasarathy - 1991
54 Boosting and rocchio applied to text filtering - Schapire, Singer et al. - 1998
43 Combining classifiers in text categorization - Larkey, Croft - 1998
36 Combining multiple evidence from different properties of wei.. (context) - Lee - 1995
29 Learning approaches for detecting and tracking news events - Yang, Carbonell et al. - 1999
29 Maximizing text-mining performance (context) - Weiss, Apte et al. - 1999
26 Multistrategy learning for information extraction - Freitag - 1998
17 A study of the overlap among document representations (context) - Katzer, McGill et al. - 1982
16 Improving text categorization methods for event tracking - Yang, Ault et al. - 2000
12 Topic tracking in a news stream - Yamron, Carp et al. - 1999
3 Topic tracking for radio (context) - Jin, Schwartz et al. - 1999
1 Improving retrieval performance by relevance feedback (context) - Proceedings, th et al. - 1990
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