| Alternate document: Details Pruning Classifiers in a Distributed Meta-Learning System (98) Andreas L. Prodromidis, Salvatore Stolfo, Philip K. Chan |
(Enter summary)
Abstract: is a powerful and portable agent-based distributed data mining system that employs metalearning
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 meta-classifier 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/prodromidis98pruning.html More
@misc{ prodromidis98pruning,
author = "A. Prodromidis and S. Stolfo",
title = "Pruning meta-classifiers in a distributed data mining system",
text = "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.",
year = "1998",
url = "citeseer.ist.psu.edu/prodromidis98pruning.html" }
Citations (may not include all citations):
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Perceptrons: An Introduction to Computation Geometry (context) - Minksy, Papert - 1988
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