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Abstract: JAM 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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14: Stacked Generalization - Wolpert - 1992
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10: Induction of Decision Trees (context) - Quinlan - 1986
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
@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/article/prodromidis98pruning.html" }
Citations (may not include all citations):2177 programs for machine learning (context) - Quinlan - 1993
1359 Induction of decision trees (context) - Quinlan - 1986 ACM DBLP
1262 Classification and Regression Trees (context) - Breiman, Friedman et al. - 1984
500 Experiments with a new boosting algorithm - Freund, Schapire - 1996 DBLP
367 Stacked generalization - Wolpert - 1992 ACM
274 Generalization as search (context) - Mitchell - 1982 DBLP
248 Fast effective rule induction - Cohen - 1995 DBLP
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137 Machine learning research: Four current directions - Dietterich - 1997
109 Stacked regressions (context) - Breiman - 1996 ACM DBLP
86 JAM: Java agents for meta-learning over distributed database.. - Stolfo, Prodromidis et al. - 1997 DBLP
85 Analysis and visualization of classifier performance: Compar.. - Provost, Fawcett - 1997 DBLP
79 Error reduction through learning multiple descriptions - Ali, Pazzani - 1996 ACM DBLP
62 Pruning adaptive boosting - Margineantu, Dietterich - 1997 ACM DBLP
57 Multiple decision trees (context) - Kwok, Carter - 1990 ACM DBLP
54 Meta-learning for multistrategy and parallel learning (context) - Chan, Stolfo - 1993
49 Combining estimates in regression and classification - LeBlanc, Tibshirani - 1993
44 Addressing the selective superiority problem: Automatic algo.. - Brodley - 1993
29 Credit card fraud detection using meta-learning: Issues and .. - Stolfo, Fan et al. - 1997
28 Using correspondence analysis to combine classifiers - Merz - 1998 ACM DBLP
28 An Extensible Meta-Learning Approach for Scalable and Accura.. - Chan - 1996 ACM
26 Sharing learned models among remote database partitions by l.. - Chan, Stolfo - 1996 DBLP
13 Creating and exploiting coverage and diversity - Brodley, Lane
9 the management of distributed learning agents - Prodromidis - 1997
8 Pattern Analysis and Mach (context) - Hansen, Salamon et al. - 1990
4 Perceptrons: An Introduction to Computation Geometry (context) - Minksy, Papert - 1988
The graph only includes citing articles where the year of publication is known.
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