Abstract
In the paper we present Rough Set approach to reasoning in incomplete information systems. We propose reduction of knowledge that eliminates only that information, which is not essential from the point of view of classification or decision making. In our approach we make only one assumption about unknown values: the real value of a missing attribute is one from the attribute domain. However, we do not assume which one. We show how to find decision rules directly from such an incomplete decision table, which are as little non-deterministic as possible and have minimal number of conditions.
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