Distributed regression for heterogeneous data sets

Yan Xing; Michael G. Madden; Jim Duggan; Gerard J. Lyons

doi:10.1007/978-3-540-45231-7_50

Distributed regression for heterogeneous data sets

Yan Xing
, Michael G. Madden
, Jim Duggan
, Gerard J. Lyons

University of Galway

Research output: Chapter in Book or Conference Publication/Proceeding › Chapter › peer-review

8 Citations (Scopus)

Abstract

Existing meta-learning based distributed data mining approaches do not explicitly address context heterogeneity across individual sites. This limitation constrains their applications where distributed data are not identically and independently distributed. Modeling heterogeneously distributed data with hierarchical models, this paper extends the traditional meta-learning techniques so that they can be successfully used in distributed scenarios with context heterogeneity.

Original language	English
Title of host publication	Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics)
Editors	Michael R. Berthold, Hans-Joachim Lenz, Elizabeth Bradley, Rudolf Kruse, Christian Borgelt
Publisher	Springer-Verlag
Pages	544-553
Number of pages	10
ISBN (Print)	3540408134, 9783540408130
DOIs	https://doi.org/10.1007/978-3-540-45231-7_50
Publication status	Published - 2003

Publication series

Name	Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics)
Volume	2810
ISSN (Print)	0302-9743
ISSN (Electronic)	1611-3349

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10.1007/978-3-540-45231-7_50

Cite this

Xing, Y., Madden, M. G., Duggan, J., & Lyons, G. J. (2003). Distributed regression for heterogeneous data sets. In M. R. Berthold, H.-J. Lenz, E. Bradley, R. Kruse, & C. Borgelt (Eds.), Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics) (pp. 544-553). (Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics); Vol. 2810). Springer-Verlag. https://doi.org/10.1007/978-3-540-45231-7_50

Xing, Yan ; Madden, Michael G. ; Duggan, Jim et al. / Distributed regression for heterogeneous data sets. Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics). editor / Michael R. Berthold ; Hans-Joachim Lenz ; Elizabeth Bradley ; Rudolf Kruse ; Christian Borgelt. Springer-Verlag, 2003. pp. 544-553 (Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics)).

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title = "Distributed regression for heterogeneous data sets",

abstract = "Existing meta-learning based distributed data mining approaches do not explicitly address context heterogeneity across individual sites. This limitation constrains their applications where distributed data are not identically and independently distributed. Modeling heterogeneously distributed data with hierarchical models, this paper extends the traditional meta-learning techniques so that they can be successfully used in distributed scenarios with context heterogeneity.",

author = "Yan Xing and Madden, \{Michael G.\} and Jim Duggan and Lyons, \{Gerard J.\}",

year = "2003",

doi = "10.1007/978-3-540-45231-7\_50",

language = "English",

isbn = "3540408134",

series = "Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics)",

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pages = "544--553",

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booktitle = "Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics)",

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Xing, Y, Madden, MG , Duggan, J & Lyons, GJ 2003, Distributed regression for heterogeneous data sets. in MR Berthold, H-J Lenz, E Bradley, R Kruse & C Borgelt (eds), Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics). Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics), vol. 2810, Springer-Verlag, pp. 544-553. https://doi.org/10.1007/978-3-540-45231-7_50

Distributed regression for heterogeneous data sets. / Xing, Yan; Madden, Michael G.; Duggan, Jim et al.
Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics). ed. / Michael R. Berthold; Hans-Joachim Lenz; Elizabeth Bradley; Rudolf Kruse; Christian Borgelt. Springer-Verlag, 2003. p. 544-553 (Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics); Vol. 2810).

Research output: Chapter in Book or Conference Publication/Proceeding › Chapter › peer-review

TY - CHAP

T1 - Distributed regression for heterogeneous data sets

AU - Xing, Yan

AU - Madden, Michael G.

AU - Duggan, Jim

AU - Lyons, Gerard J.

PY - 2003

Y1 - 2003

N2 - Existing meta-learning based distributed data mining approaches do not explicitly address context heterogeneity across individual sites. This limitation constrains their applications where distributed data are not identically and independently distributed. Modeling heterogeneously distributed data with hierarchical models, this paper extends the traditional meta-learning techniques so that they can be successfully used in distributed scenarios with context heterogeneity.

AB - Existing meta-learning based distributed data mining approaches do not explicitly address context heterogeneity across individual sites. This limitation constrains their applications where distributed data are not identically and independently distributed. Modeling heterogeneously distributed data with hierarchical models, this paper extends the traditional meta-learning techniques so that they can be successfully used in distributed scenarios with context heterogeneity.

UR - https://www.scopus.com/pages/publications/26944448756

U2 - 10.1007/978-3-540-45231-7_50

DO - 10.1007/978-3-540-45231-7_50

M3 - Chapter

AN - SCOPUS:26944448756

SN - 3540408134

SN - 9783540408130

T3 - Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics)

SP - 544

EP - 553

BT - Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics)

A2 - Berthold, Michael R.

A2 - Lenz, Hans-Joachim

A2 - Bradley, Elizabeth

A2 - Kruse, Rudolf

A2 - Borgelt, Christian

PB - Springer-Verlag

ER -

Xing Y, Madden MG , Duggan J, Lyons GJ. Distributed regression for heterogeneous data sets. In Berthold MR, Lenz HJ, Bradley E, Kruse R, Borgelt C, editors, Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics). Springer-Verlag. 2003. p. 544-553. (Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics)). doi: 10.1007/978-3-540-45231-7_50

Distributed regression for heterogeneous data sets

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