Extracting Rules from Data with Exceptions


In this paper a method of extracting typical properties from a set of data containing exceptions is discussed. An observational function classifies a sample, removes the minority elements, and extracts a general rule based on the remaining elements. Furthermore, the extracted rule is improved by statistical estimation when new data are added. This technique is applied to a system for aiding the construction of knowledge bases.

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