Concept simplification and prediction accuracy

摘要: A recently reported phenomenon in machine concept learning is that descriptions can be simplified with little ill-effect (or even positive effects) on classification accuracy, but there has been qualification of this observation. Experiments using Quinlan's from examples system, ID3, and Fisher's conceptual clustering COBWEB, suggest the benefits simplification vary amount training statistical dependence members defining attributes.