Testing of Inductive Preprocessing Algorithm
The result's identifiers
Result code in IS VaVaI
<a href="https://www.isvavai.cz/riv?ss=detail&h=RIV%2F68407700%3A21230%2F09%3A00159932" target="_blank" >RIV/68407700:21230/09:00159932 - isvavai.cz</a>
Alternative codes found
RIV/68407700:21240/09:00159932
Result on the web
<a href="http://citeseerx.ist.psu.edu/viewdoc/download?doi=10.1.1.215.1155&rep=rep1&type=pdf" target="_blank" >http://citeseerx.ist.psu.edu/viewdoc/download?doi=10.1.1.215.1155&rep=rep1&type=pdf</a>
DOI - Digital Object Identifier
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Alternative languages
Result language
angličtina
Original language name
Testing of Inductive Preprocessing Algorithm
Original language description
The data preprocessing is very important part of the knowledge discovery process. Data mining systems contains tens of preprocessing methods (for example methods for missing data imputation, data reduction, discretization, data enrichment, etc...) and usually it is not clear which methods to use. The selection of preprocessing methods appropriate for particular dataset needs strong experience and a lot of experimenting. In this paper we will test our extension of inductive approach to data preprocessing. We developed inductive preprocessing method which utilizes genetic algorithm to compose from scratch a sequence of preprocessing methods which fits to the data and allows successful model to be created. To test our automatic preprocessing utilize several real-world datasets available from UCI Machine learning repository.
Czech name
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Czech description
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Classification
Type
O - Miscellaneous
CEP classification
IN - Informatics
OECD FORD branch
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Result continuities
Project
<a href="/en/project/KJB201210701" target="_blank" >KJB201210701: Automated Knowledge Extraction</a><br>
Continuities
Z - Vyzkumny zamer (s odkazem do CEZ)
Others
Publication year
2009
Confidentiality
S - Úplné a pravdivé údaje o projektu nepodléhají ochraně podle zvláštních právních předpisů