Fast unsupervised online drift detection using incremental kolmogorov-smirnov test

Denis Dos Reis; Peter Flach; Stan Matwin; Gustavo Batista

doi:10.1145/2939672.2939836

Fast unsupervised online drift detection using incremental kolmogorov-smirnov test

Denis Dos Reis, Peter Flach, Stan Matwin, Gustavo Batista

Research output: Chapter in Book/Report/Conference proceeding › Conference contribution

Original language	English
Title of host publication	KDD 2016 - Proceedings of the 22nd ACM SIGKDD International Conference on Knowledge Discovery and Data Mining
Publisher	Association for Computing Machinery
Pages	1545-1554
Number of pages	10
ISBN (Electronic)	9781450342322
DOIs	https://doi.org/10.1145/2939672.2939836
Publication status	Published - Aug 13 2016
Externally published	Yes
Event	22nd ACM SIGKDD International Conference on Knowledge Discovery and Data Mining, KDD 2016 - San Francisco, United States Duration: Aug 13 2016 → Aug 17 2016

Publication series

Name	Proceedings of the ACM SIGKDD International Conference on Knowledge Discovery and Data Mining
Volume	13-17-August-2016

Conference

Conference	22nd ACM SIGKDD International Conference on Knowledge Discovery and Data Mining, KDD 2016
Country/Territory	United States
City	San Francisco
Period	8/13/16 → 8/17/16

ASJC Scopus Subject Areas

Software
Information Systems

Keywords

Cartesian tree
Concept drift
Data stream
Kolmogorov-Smirnov
Lazy propagation
Treap

Access to Document

10.1145/2939672.2939836

Cite this

Dos Reis, D., Flach, P., Matwin, S., & Batista, G. (2016). Fast unsupervised online drift detection using incremental kolmogorov-smirnov test. In KDD 2016 - Proceedings of the 22nd ACM SIGKDD International Conference on Knowledge Discovery and Data Mining (pp. 1545-1554). (Proceedings of the ACM SIGKDD International Conference on Knowledge Discovery and Data Mining; Vol. 13-17-August-2016). Association for Computing Machinery. https://doi.org/10.1145/2939672.2939836

Fast unsupervised online drift detection using incremental kolmogorov-smirnov test. / Dos Reis, Denis; Flach, Peter; Matwin, Stan et al.
KDD 2016 - Proceedings of the 22nd ACM SIGKDD International Conference on Knowledge Discovery and Data Mining. Association for Computing Machinery, 2016. p. 1545-1554 (Proceedings of the ACM SIGKDD International Conference on Knowledge Discovery and Data Mining; Vol. 13-17-August-2016).

Research output: Chapter in Book/Report/Conference proceeding › Conference contribution

Dos Reis, D, Flach, P, Matwin, S & Batista, G 2016, Fast unsupervised online drift detection using incremental kolmogorov-smirnov test. in KDD 2016 - Proceedings of the 22nd ACM SIGKDD International Conference on Knowledge Discovery and Data Mining. Proceedings of the ACM SIGKDD International Conference on Knowledge Discovery and Data Mining, vol. 13-17-August-2016, Association for Computing Machinery, pp. 1545-1554, 22nd ACM SIGKDD International Conference on Knowledge Discovery and Data Mining, KDD 2016, San Francisco, United States, 8/13/16. https://doi.org/10.1145/2939672.2939836

Dos Reis D, Flach P, Matwin S, Batista G. Fast unsupervised online drift detection using incremental kolmogorov-smirnov test. In KDD 2016 - Proceedings of the 22nd ACM SIGKDD International Conference on Knowledge Discovery and Data Mining. Association for Computing Machinery. 2016. p. 1545-1554. (Proceedings of the ACM SIGKDD International Conference on Knowledge Discovery and Data Mining). doi: 10.1145/2939672.2939836

Dos Reis, Denis ; Flach, Peter ; Matwin, Stan et al. / Fast unsupervised online drift detection using incremental kolmogorov-smirnov test. KDD 2016 - Proceedings of the 22nd ACM SIGKDD International Conference on Knowledge Discovery and Data Mining. Association for Computing Machinery, 2016. pp. 1545-1554 (Proceedings of the ACM SIGKDD International Conference on Knowledge Discovery and Data Mining).

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Fast unsupervised online drift detection using incremental kolmogorov-smirnov test

Publication series

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ASJC Scopus Subject Areas

Keywords

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