Learning Uncertain Rules with CondorCKD

摘要

CondorCKD is a system implementing a novel approach to discovering knowledge from data. It addresses the issue of relevance of the learned rules by algebraic means and explicitly supports the subsequent processing by probabilistic reasoning. After briefly summarizing the key ideas underlying CondorCKD, the purpose of this paper is to present a walk-through and system demonstration.