Linguistic Attribute Hierarchies for Downwards Propagation of Information
Hongmei He, Jonathan Lawry · 2008
We investigate the propagation of label informa tion for multi-attribute decision maldng problems downwards a linguistic attribute hierarchy, which represents the complex and often imprecise functional relationships between low level attributes or measurements and high-level decision or classification variables. The downward propagation algorithm identifies the branches in linguistic decision trees for which the probability of a high-level goal exceeds a given threshold. The sensitivity of the method to this threshold is then reduced by integrating with respect to a probability distribution on high threshold values.