AUTHORS: A. Rontogiannis and N. J. Dimopoulos
	 
TITLE:   A Probabilistic Approach for Reducing the Search Cost
	 in Binary Decision Trees
	 
IN: 	 Proceedings of the IEEE Pacific Rim Conference 
	 on Communications Computers and Signal Processing, 
	 Victoria, B.C., May 19-21, 1993. 


ABSTRACT

In this work we present a probabilistic model for reducing the number
of decisions (tests) that are required in a particular diagnostic 
procedure. Specifically, we consider that a problem is structured as a 
binary balanced decision tree the interior nodes of which represent test 
points; the paths of the tree correspond to different diagnoses. By 
assuming that there exists sufficient probabilistic information available 
concerning the decisions at the interior nodes, we attempt to minimize 
the average number of these decisions when we search for a final 
diagnosis.