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Cohesion methods in inductive learning
Author(s) -
Abbott Lynn
Publication year - 1987
Publication title -
computational intelligence
Language(s) - English
Resource type - Journals
SCImago Journal Rank - 0.353
H-Index - 52
eISSN - 1467-8640
pISSN - 0824-7935
DOI - 10.1111/j.1467-8640.1987.tb00214.x
Subject(s) - cohesion (chemistry) , inductive reasoning , inductive bias , computer science , artificial intelligence , machine learning , multi task learning , engineering , chemistry , organic chemistry , systems engineering , task (project management)
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.