Boolean factor analysis for data preprocessing in machine learning
The result's identifiers
Result code in IS VaVaI
<a href="https://www.isvavai.cz/riv?ss=detail&h=RIV%2F61989592%3A15310%2F10%3A10216523" target="_blank" >RIV/61989592:15310/10:10216523 - 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
Boolean factor analysis for data preprocessing in machine learning
Original language description
We present two input data preprocessing methods for machine learning (ML). The first one consists in extending the set of attributes describing objects in input data table by new attributes and the second one consists in replacing the attributes by new attributes. The methods utilize formal concept analysis (FCA) and boolean factor analysis, recently described by FCA, in that the new attributes are defined by so-called factor concepts computed from input data table. The methods are demonstrated on decision tree induction. The experimental evaluation and comparison of performance of decision trees induced from original and preprocessed input data is performed with standard decision tree induction algorithms ID3 and C4.5 on several benchmark datasets.
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
<a href="/en/project/GPP202%2F10%2FP360" target="_blank" >GPP202/10/P360: Classification with use of formal concept analysis</a><br>
Continuities
P - Projekt vyzkumu a vyvoje financovany z verejnych zdroju (s odkazem do CEP)
Others
Publication year
2010
Confidentiality
S - Úplné a pravdivé údaje o projektu nepodléhají ochraně podle zvláštních právních předpisů
Data specific for result type
Article name in the collection
Proceedings of ICMLA 2010
ISBN
978-0-7695-4300-0
ISSN
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e-ISSN
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Number of pages
4
Pages from-to
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Publisher name
IEEE
Place of publication
Washington DC
Event location
Washington, D.C., USA
Event date
Dec 12, 2010
Type of event by nationality
WRD - Celosvětová akce
UT code for WoS article
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