Algorithm for Missing Values Imputation in Categorical Data with Use of Association Rules
The result's identifiers
Result code in IS VaVaI
<a href="https://www.isvavai.cz/riv?ss=detail&h=RIV%2F68407700%3A21110%2F11%3A00190305" target="_blank" >RIV/68407700:21110/11:00190305 - isvavai.cz</a>
Result on the web
<a href="http://www.searchdl.org/index.php/journalclient/viewpaper/6/0/10/1/22/59/3/" target="_blank" >http://www.searchdl.org/index.php/journalclient/viewpaper/6/0/10/1/22/59/3/</a>
DOI - Digital Object Identifier
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Alternative languages
Result language
angličtina
Original language name
Algorithm for Missing Values Imputation in Categorical Data with Use of Association Rules
Original language description
This paper presents new algorithm for missing values imputation in categorical data. The algorithm is based on using association rules and is presented in three variants. Experimental shows better accuracy of missing values imputation using new algorithmthen using most common attribute value.
Czech name
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Czech description
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Classification
Type
J<sub>x</sub> - Unclassified - Peer-reviewed scientific article (Jimp, Jsc and Jost)
CEP classification
IN - Informatics
OECD FORD branch
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Result continuities
Project
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Continuities
S - Specificky vyzkum na vysokych skolach<br>I - Institucionalni podpora na dlouhodoby koncepcni rozvoj vyzkumne organizace
Others
Publication year
2011
Confidentiality
S - Úplné a pravdivé údaje o projektu nepodléhají ochraně podle zvláštních právních předpisů
Data specific for result type
Name of the periodical
International Journal on Recent Trends in Engineering & Technology [IJRTET]
ISSN
2158-5563
e-ISSN
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Volume of the periodical
6
Issue of the periodical within the volume
1
Country of publishing house
US - UNITED STATES
Number of pages
4
Pages from-to
111-114
UT code for WoS article
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EID of the result in the Scopus database
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