Decision Tree Creation Methodology Using Propositionalized Attributes

Grabusts Pēteris, Borisovs Arkādijs and Aleksejeva Ludmila
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Grabusts Pēteris: Rezekne Academy of Technologies, Latvia
Aleksejeva Ludmila: Riga Technical University, Latvia

Information Technology and Management Science, 2016, vol. 19, issue 1, 34-38

Abstract: The aim of the article is to analyse and thoroughly research the methods of construction of the decision trees that use decision tree learning with statement propositionalized attributes. Classical decision tree learning algorithms, as well as decision tree learning with propositionalized attributes have been observed. The article provides the detailed analysis of one of the methodologies on the importance of using the decision trees in knowledge presentation. The concept of ontology use is offered to develop classification systems of decision trees. The application of the methodology would allow improving the classification accuracy.

Keywords: Decision tree; ontology; propositionalization; taxonomy (search for similar items in EconPapers)
Date: 2016
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Persistent link: https://EconPapers.repec.org/RePEc:vrs:itmasc:v:19:y:2016:i:1:p:34-38:n:8

DOI: 10.1515/itms-2016-0008

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