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Abstract: There has been considerable interest recently in various approaches to scaling up machine learning systems to large and distributed data sets. We have been studying approaches based upon the parallel application of multiple learning programs at distributed sites, followed by a meta-learning stage to combine the multiple models in a principled fashion. In this paper, we empirically determine the "best" data partitioning scheme for a selected data set to compose "appropriatelysized " subsets and... (Update)
Context of citations to this paper: More
.... domain are not immediately discernible, but rather requires extensive experimentation to find the best models, and the best meta classifiers [20]. 2.3 Cost based Models for Fraud Detection Most of the machine learning literature concentrates on model accuracy (either training...
...even with a complete analysis [45, 46] in the ROC space. 6 Extensive experiments evaluating di erent data distributions are presented in [42]. 26 local and 50 internal classi ers (those imported from their peer data sites) each site also imported 60 external classi ers...
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BibTeX entry: (Update)
A.L. Prodromidis and S.J. Stolfo. A comparative evaluation of meta-learning strategies over large and distributed data sets. In Workshop on Meta-learning, Sixteenth Intl. Conf. Machine Learning, 1999. Submitted for publication. http://citeseer.ist.psu.edu/prodromidis99comparative.html More
@misc{ prodromidis99comparative,
author = "A. Prodromidis and S. Stolfo",
title = "A comparative evaluation of meta-learning strategies over large and distributed
data sets",
text = "A.L. Prodromidis and S.J. Stolfo. A comparative evaluation of meta-learning
strategies over large and distributed data sets. In Workshop on Meta-learning,
Sixteenth Intl. Conf. Machine Learning, 1999. Submitted for publication.",
year = "1999",
url = "citeseer.ist.psu.edu/prodromidis99comparative.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
537 A theory of the learnable (context) - Valiant - 1984 ACM DBLP
454 the uniform convergence of relative frequencies of events to.. (context) - Vapnik, Chervonenkis - 1971
367 Stacked generalization - Wolpert - 1992 ACM
261 The weighted majority algorithm - Littlestone, Warmuth - 1989 ACM DBLP
248 An Introduction to computational learning theory (context) - Kearns, Vazirani - 1994 ACM
87 ective rule induction (context) - Cohen - 1995
85 Analysis and visualization of classifier performance: Compar.. - Provost, Fawcett - 1997
85 Bounds on the sample complexity of bayesian learning using i.. - Kearns, Haussler et al. - 1994 ACM DBLP
71 A comparative evaluation of voting and meta-learning on part.. - Chan, Stolfo - 1995 DBLP
62 Megainduction: machine learning on very large databases (context) - Catlett - 1992
58 Statistical mechanics of learning from examples (context) - Seung, Sompolinsky et al. - 1992
54 Cost-sensitive classification: Empirical evaluation of a hyd.. - Turney - 1995
54 Meta-learning for multistrategy and parallel learning (context) - Chan, Stolfo - 1993
47 Megainduction: A test flight (context) - Catlett - 1991 DBLP
47 Theory and Application of Correspondence Analysis (context) - Greenacre - 1984
42 Computational learning theory: An Introduction (context) - Anthony, Biggs - 1992
36 Toward scalable learning with non-uniform class and cost dis.. - Chan, Stolfo - 1998 DBLP
33 Robust classification systems for imprecise environments - Provost, Fawcett - 1998
28 Using correspondence analysis to combine classifiers - Merz - 1998
17 Working Notes for the AAAI-96 Workshop on Integrating Multip.. (context) - Chan, Stolfo et al. - 1996
17 Pruning meta-classifiers in a distributed data mining system - Prodromidis, Stolfo - 1998
10 Scaling up inductive algorithms: An overview - Provost, Kolluri - 1997
9 Agent-based distributed learning applied to fraud detection - Prodromidis, Stolfo
2 Large datasets lead to overly complex models: As explanation.. (context) - Jensen, Oates - 1998
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