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Decision Tree Creation Methodology Using Propositionalized Attributes

Author

Listed:
  • Grabusts Pēteris

    (Rezekne Academy of Technologies, Latvia)

  • Borisovs Arkādijs
  • Aleksejeva Ludmila

    (Riga Technical University, Latvia)

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.

Suggested Citation

  • Grabusts Pēteris & Borisovs Arkādijs & Aleksejeva Ludmila, 2016. "Decision Tree Creation Methodology Using Propositionalized Attributes," Information Technology and Management Science, Sciendo, vol. 19(1), pages 34-38, December.
    • Handle: RePEc:vrs:itmasc:v:19:y:2016:i:1:p:34-38:n:8
    DOI: 10.1515/itms-2016-0008
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