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Abstract: JAM is a powerful and portable agent-based distributed data mining system that employs meta-learning techniques to integrate a number of independent classifiers (models) derived in parallel from independent and (possibly) inherently distributed databases. Although meta-learning promotes scalability and accuracy in a simple and straightforward manner, brute force meta-learning techniques can result in large, redundant, inefficient and some times inaccurate metaclassifier hierarchies. In this... (Update)
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BibTeX entry: (Update)
A. L. Prodromidis and S. J. Stolfo. Pruning meta-classifiers in a distributed data mining system. In In Proc of the First National Conference on New Information Technologies, pages 151--160, Athens, Greece, October 1998. http://citeseer.ist.psu.edu/article/prodromidis98pruning.html More
@inproceedings{ prodromidis98pruning,
author = "A. Prodromidis and S. Stolfo",
title = "Pruning meta-classifiers in a distributed data mining system",
booktitle = "Proc of the First National Conference on New Information
Technologies",
pages = "151--160",
address = "Athens, Greece",
month = oct,
year = "1998",
url = "citeseer.ist.psu.edu/article/prodromidis98pruning.html" }
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