Robustness of High-Dimensional Data Mining
The result's identifiers
Result code in IS VaVaI
<a href="https://www.isvavai.cz/riv?ss=detail&h=RIV%2F67985807%3A_____%2F14%3A00432406" target="_blank" >RIV/67985807:_____/14:00432406 - isvavai.cz</a>
Result on the web
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DOI - Digital Object Identifier
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Alternative languages
Result language
angličtina
Original language name
Robustness of High-Dimensional Data Mining
Original language description
Standard data mining procedures are sensitive to the presence of outlying measurements in the data. This work has the aim to propose robust versions of some existing data mining procedures, i.e. methods resistant to outliers. In the area of classification analysis, we propose a new robust method based on a regularized version of the minimum weighted covariance determinant estimator. The method is suitable for data with the number of variables exceeding the number of observations. The method is based onimplicit weights assigned to individual observations. Our approach is a unique attempt to combine regularization and high robustness, allowing to downweight outlying high-dimensional observations. Classification performance of new methods and some ideasconcerning classification analysis of high-dimensional data are illustrated on real raw data as well as on data contaminated by severe outliers.
Czech name
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Czech description
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Classification
Type
D - Article in proceedings
CEP classification
IN - Informatics
OECD FORD branch
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Result continuities
Project
Result was created during the realization of more than one project. More information in the Projects tab.
Continuities
I - Institucionalni podpora na dlouhodoby koncepcni rozvoj vyzkumne organizace
Others
Publication year
2014
Confidentiality
S - Úplné a pravdivé údaje o projektu nepodléhají ochraně podle zvláštních právních předpisů
Data specific for result type
Article name in the collection
ITAT 2014. Information Technologies - Applications and Theory. Part II
ISBN
978-80-87136-19-5
ISSN
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e-ISSN
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Number of pages
8
Pages from-to
53-60
Publisher name
Institute of Computer Science AS CR
Place of publication
Prague
Event location
Demänovská dolina
Event date
Sep 25, 2014
Type of event by nationality
EUR - Evropská akce
UT code for WoS article
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