Decision and inhibitory trees and rules for decision tables with many-valued decisions
Auteur :
Alsolami, Fawaz / Azad, Mohammad / Chikalov, Igor / Moshkov, Mikhail
Éditeur :
Springer Nature Switzerland AG
ISBN :
9783030128562
Date de publication :
27 nov. 2020
Dimensions :
23,5 x 15,5 cm
Langue :
Anglais
Pays d'origine :
Suisse
The results presented here (including the assessment of a new tool – inhibitory trees) offer valuable tools for researchers in the areas of data mining, knowledge discovery, and machine learning, especially those whose work involves decision tables with many-valued decisions.