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.