Decision Tree Creation Methodology Using Propositionalized Attributes
Information Technology and Management Science
2016
Pēteris Grabusts,
Arkādijs Borisovs,
Ludmila Aleksejeva
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
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.
Grabusts, P., Borisovs, A., Aleksejeva, L. Decision Tree Creation Methodology Using Propositionalized Attributes. Information Technology and Management Science, 2016, Vol. 19, pp. 34-38. ISSN 2255-9086. e-ISSN 2255-9094.
Publication language
English (en)