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 REFERENCES
Note: OCR errors may be found in this Reference List extracted from the full text article. ACM has opted to expose the complete List rather than only correct and linked references.
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[1] P. Chan, S. S., and D. Wolpert, editors. Proceedings of the AAAI-96 Workshop on Integrating Multiple Learned Models, Portland OR., 1996. AAAI.
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[2] J. Chattratichat, J. Darlington, Y. Guo, S. Hedvall, M. Khler, J. S. A. Saleem, and D. Yang. Deploying enterprise data mining on the internet. In PAKDD, 1998. http://ruby.doc.ic.ac.uk/.
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[3] P. Domingos. Knowledge discovery via multiple models. International Data Analysis, 1998.
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[4] R. L. Grossman, S. Kasif, D. Mon, A. Ramu, and B. Malhi. The preliminary design of papyrus: A system for high performance, distributed data mining over clusters, meta-clusters and super-clusters. In Kargupta et al. [6]. http://www.lac.uic.edu/~grossman/cv/ dataspace-background.htm.
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[5] O. Günther, R. Koerstein, R. Krishnan, R. Müller, and P. Schmidt. The mmm project: Access to algorithms via www. In Poster presented at the Third International World-Wide Web Conference, Germany, 1995. http: //macke.wiwi.hu-berlin.de/mmm/.
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[6] H. Kargupta et al., editors. Workshop on Distributed Data Mining, The Fourth International Conference on Knowledge Discovery and Data Mining, 1998. http:// www.eecs.wsu.edu/~hillol/kdd98ws.html.
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[7] H. Kargupta and B. Park. The collective data mining: A technology for ubiquitous data analysis from distributed heterogeneous sites. Submitted to IEEE Computer Special Issue on Data Mining, 1998. http: //www.eecs.wsu.edu/~hillol/ddm.html.
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Mark G. Kelly , David J. Hand , Niall M. Adams, The impact of changing populations on classifier performance, Proceedings of the fifth ACM SIGKDD international conference on Knowledge discovery and data mining, p.367-371, August 15-18, 1999, San Diego, California, United States
[doi> 10.1145/312129.312285]
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[9] P. Chan and S. Stolfo. Toward parallel and distributed learning by meta-learning. In Proceedings of the Second International Workshop on Multistrategy Learning, pages 15-165, 1993.
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[10] A. Prodromidis, P. Chan, and S. Stolfo. Meta-learning in distributed data mining systems: Issues and approaches. In Proc. of the 3rd Int'l Conf. on Knowledge Discovery and Data Mining, 1997.
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[12] S. Stolfo, A. Prodromidis, S. Tselepis, W. Lee, D. Fan, and P. Chan. JAM: Java agents for meta-learning over distributed databases. In Proceedings of the Third International Conference on Knowledge Discovery and Data Mining, 1997. http://www.cs.columbia.edu/ ~sal/JAM/PROJECT/.
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[13] A. S. Weigend and D. A. Nix. Predictions with confidence intervals (local error bars). ICONIP, Seoul, 1994.
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