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Robust datamining

Uwe, Aickelin

Authors

Aickelin Uwe



Abstract

Our long-term research goal is to develop datamining methodologies that are robust to changes in data and uncertainty. By robust we mean solutions remain ‘optimal’ when things change or are easily repaired. Broadly, this robustness can be achieved in two ways: One, by having ‘slack’ in the solution or two, by constructing the solution such that is easily repairable, e.g. failures are isolated.

Citation

Uwe, A. (2017). Robust datamining

Conference Name 4th Asia Pacific Conference on Advanced Research (APCAR - Mar, 2017)
End Date Mar 5, 2017
Acceptance Date Feb 1, 2017
Publication Date Mar 5, 2017
Deposit Date Nov 15, 2017
Publicly Available Date Nov 15, 2017
Journal 4th Asia Pacific Conference on Advanced Research (APCAR- MAR 2017), Melbourne, Australia
Peer Reviewed Peer Reviewed
Public URL http://eprints.nottingham.ac.uk/id/eprint/48066
Related Public URLs http://apiar.org.au/?conference=4th-asia-pacific-conference-on-advanced-research-apcar-mar-2017-melbourne-australia
Copyright Statement Copyright information regarding this work can be found at the following address: http://eprints.nottingham.ac.uk/end_user_agreement.pdf
Additional Information Proceedings published by Asia Pacific Institute of Advanced Research. ISBN 9780995398009 / ISSN 2207-2799

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Copyright Statement
Copyright information regarding this work can be found at the following address: http://eprints.nottingham.ac.uk/end_user_agreement.pdf





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