OUTLIER DETECTION TECHNIQUES IN MULTIDIMENSIONAL DATASETS

Result code in IS VaVaI
<a href="https://www.isvavai.cz/riv?ss=detail&h=RIV%2F49777513%3A23520%2F20%3A43958910" target="_blank" >RIV/49777513:23520/20:43958910 - isvavai.cz</a>
Result on the web
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DOI - Digital Object Identifier
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Result language
angličtina
Original language name
OUTLIER DETECTION TECHNIQUES IN MULTIDIMENSIONAL DATASETS
Original language description
Outliers can significantly impact data summarization results and data analysis across all types of data analysis. Identifying outliers in multidimensional data is, therefore, one of the key approaches in data preprocessing. across all types of data analysis. In this article, we present several univariate and multivariate methods for the identification of outliers in multidimensional data.
Czech name
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Czech description
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Project
<a href="/en/project/LO1506" target="_blank" >LO1506: Sustainability support of the centre NTIS - New Technologies for the Information Society</a><br>
Continuities
P - Projekt vyzkumu a vyvoje financovany z verejnych zdroju (s odkazem do CEP)<br>I - Institucionalni podpora na dlouhodoby koncepcni rozvoj vyzkumne organizace

Publication year
2020
Confidentiality
S - Úplné a pravdivé údaje o projektu nepodléhají ochraně podle zvláštních právních předpisů

Article name in the collection
19th Conference on Applied Mathematics, APLIMAT 2020 - Proceedings
ISBN
978-80-227-4983-1
ISSN
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e-ISSN
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Number of pages
7
Pages from-to
942-948
Publisher name
SPEKTRUM STU
Place of publication
Bratislava
Event location
Bratislava, Slovensko
Event date
Feb 4, 2020
Type of event by nationality
WRD - Celosvětová akce
UT code for WoS article
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