Modeling concept drift: A probabilistic graphical model based approach

Hanen Borchani; Ana Maria Martinez; Andrés R. Masegosa; Helge Langseth; Thomas Dyhre Nielsen; Antonio Salmerón; Antonio Fernández; Anders Læsø Madsen; Ramón Sáez

doi:10.1007/978-3-319-24465-5_7

Modeling concept drift: A probabilistic graphical model based approach

Hanen Borchani, Ana Maria Martinez, Andrés R. Masegosa, Helge Langseth, Thomas Dyhre Nielsen, Antonio Salmerón, Antonio Fernández, Anders Læsø Madsen, Ramón Sáez

Institut for Datalogi

Publikation: Bidrag til bog/antologi/rapport/konference proceeding › Konferenceartikel i proceeding › Forskning › peer review

17 Citationer (Scopus)

727 Downloads (Pure)

Abstract

An often used approach for detecting and adapting to concept drift when doing classification is to treat the data as i.i.d. and use changes in classification accuracy as an indication of concept drift. In this paper, we take a different perspective and propose a framework, based on probabilistic graphical models, that explicitly represents concept drift using latent variables. To ensure efficient inference and learning, we re- sort to a variational Bayes inference scheme. As a proof of concept, we demonstrate and analyze the proposed framework using synthetic data sets as well as a real financial data set from a Spanish bank.

Originalsprog	Engelsk
Titel	Advances in Intelligent Data Analysis XIV : 14th International Symposium, IDA 2015, Saint Etienne. France, October 22 -24, 2015. Proceedings
Redaktører	Elisa Fromont, Tijl De Bie, Matthijs van Leeuwen
Forlag	Springer
Publikationsdato	2015
Sider	72-83
ISBN (Trykt)	978-3-319-24464-8
ISBN (Elektronisk)	978-3-319-24465-5
DOI	https://doi.org/10.1007/978-3-319-24465-5_7
Status	Udgivet - 2015
Begivenhed	International Symposium, IDA 2015 - Saint Etienne, Frankrig Varighed: 22 okt. 2015 → 24 okt. 2015 Konferencens nummer: 14th

Konference

Konference	International Symposium, IDA 2015
Nummer	14th
Land/Område	Frankrig
By	Saint Etienne
Periode	22/10/2015 → 24/10/2015

Navn	Lecture Notes in Computer Science
Nummer	9385
ISSN	0302-9743

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10.1007/978-3-319-24465-5_7

ida_2015Indsendt manuskript, 368 KB

AUB Link

Søg efter materialet i Aalborg Universitetsbiblioteks søgemaskine

AMIDST: Analysis of MassIve Data STreams - AMIDST
Madsen, A. L., Rommerdahl Bock, A., Nielsen, T. D. & Martinez, A. M.
European Union’s Seventh Framework Programme for research, technological development and demonstration
01/01/2014 → 31/12/2016
Projekter: Projekt › Forskning

Citationsformater

Borchani, H., Martinez, A. M., Masegosa, A. R., Langseth, H., Nielsen, T. D., Salmerón, A., Fernández, A., Madsen, A. L., & Sáez, R. (2015). Modeling concept drift: A probabilistic graphical model based approach. I E. Fromont, T. De Bie, & M. van Leeuwen (red.), Advances in Intelligent Data Analysis XIV: 14th International Symposium, IDA 2015, Saint Etienne. France, October 22 -24, 2015. Proceedings (s. 72-83). Springer. https://doi.org/10.1007/978-3-319-24465-5_7

Borchani, Hanen ; Martinez, Ana Maria ; Masegosa, Andrés R. et al. / Modeling concept drift : A probabilistic graphical model based approach. Advances in Intelligent Data Analysis XIV: 14th International Symposium, IDA 2015, Saint Etienne. France, October 22 -24, 2015. Proceedings. red. / Elisa Fromont ; Tijl De Bie ; Matthijs van Leeuwen. Springer, 2015. s. 72-83 (Lecture Notes in Computer Science; Nr. 9385).

@inproceedings{e79a299c4f5a4df98b246a035472af30,

title = "Modeling concept drift: A probabilistic graphical model based approach",

abstract = "An often used approach for detecting and adapting to concept drift when doing classification is to treat the data as i.i.d. and use changes in classification accuracy as an indication of concept drift. In this paper, we take a different perspective and propose a framework, based on probabilistic graphical models, that explicitly represents concept drift using latent variables. To ensure efficient inference and learning, we re- sort to a variational Bayes inference scheme. As a proof of concept, we demonstrate and analyze the proposed framework using synthetic data sets as well as a real financial data set from a Spanish bank.",

author = "Hanen Borchani and Martinez, {Ana Maria} and Masegosa, {Andr{\'e}s R.} and Helge Langseth and Nielsen, {Thomas Dyhre} and Antonio Salmer{\'o}n and Antonio Fern{\'a}ndez and Madsen, {Anders L{\ae}s{\o}} and Ram{\'o}n S{\'a}ez",

year = "2015",

doi = "10.1007/978-3-319-24465-5_7",

language = "English",

isbn = "978-3-319-24464-8",

series = "Lecture Notes in Computer Science",

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Borchani, H, Martinez, AM, Masegosa, AR, Langseth, H, Nielsen, TD, Salmerón, A, Fernández, A, Madsen, AL & Sáez, R 2015, Modeling concept drift: A probabilistic graphical model based approach. i E Fromont, T De Bie & M van Leeuwen (red), Advances in Intelligent Data Analysis XIV: 14th International Symposium, IDA 2015, Saint Etienne. France, October 22 -24, 2015. Proceedings. Springer, Lecture Notes in Computer Science, nr. 9385, s. 72-83, International Symposium, IDA 2015, Saint Etienne, Frankrig, 22/10/2015. https://doi.org/10.1007/978-3-319-24465-5_7

Modeling concept drift: A probabilistic graphical model based approach. / Borchani, Hanen; Martinez, Ana Maria; Masegosa, Andrés R. et al.
Advances in Intelligent Data Analysis XIV: 14th International Symposium, IDA 2015, Saint Etienne. France, October 22 -24, 2015. Proceedings. red. / Elisa Fromont; Tijl De Bie; Matthijs van Leeuwen. Springer, 2015. s. 72-83 (Lecture Notes in Computer Science; Nr. 9385).

Publikation: Bidrag til bog/antologi/rapport/konference proceeding › Konferenceartikel i proceeding › Forskning › peer review

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AU - Salmerón, Antonio

AU - Fernández, Antonio

AU - Madsen, Anders Læsø

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Borchani H, Martinez AM, Masegosa AR, Langseth H, Nielsen TD, Salmerón A et al. Modeling concept drift: A probabilistic graphical model based approach. I Fromont E, De Bie T, van Leeuwen M, red., Advances in Intelligent Data Analysis XIV: 14th International Symposium, IDA 2015, Saint Etienne. France, October 22 -24, 2015. Proceedings. Springer. 2015. s. 72-83. (Lecture Notes in Computer Science; Nr. 9385). doi: 10.1007/978-3-319-24465-5_7

Modeling concept drift: A probabilistic graphical model based approach

Abstract

Konference

Adgang til dokumentet

AUB Link

Fingeraftryk

Projekter

AMIDST: Analysis of MassIve Data STreams - AMIDST

Citationsformater