Cohesion methods in inductive learning
Lynn Abbott · Computational Intelligence · 1987
According to Webster, cohesion is “the act or process of sticking together tightly.” Here the term represents the underlying forces that drive the formation of classes during inductive learning. This paper considers several numerical and conceptual induction algorithms, and compares their methods of cohesion. While these algorithms represent several different methods, they also exhibit some significant commonalities.