Title :
Fuzzy hypothesis trees and decision making
Author :
Mohiddin, S.M. ; Saunders, D.I.
Author_Institution :
Dept. of Comput. Sci., Queen Mary & Westfield Coll., London, UK
Abstract :
A new interpretation of decision tree induction is provided. A method is suggested to infer the class of an object using fuzzy relations. It is shown that this new method has several advantages over previous ones in knowledge representation. It can handle vague and incomplete evidence to correctly classify the objects. The problem of unknown evidence is also representable in a uniform way
Keywords :
decision support systems; fuzzy logic; inference mechanisms; learning systems; trees (mathematics); decision tree induction; fuzzy hypothesis trees; fuzzy relations; incomplete evidence; knowledge representation; unknown evidence;
Conference_Titel :
Intelligent Decision Support Systems and Medicine, IEE Colloquium on
Conference_Location :
London
