Abstract
The number of features are quite high in many fields. For instance, the number of symptoms are around thousands in probabilistic medical expert systems. Since it is not practical to query all the symptoms to reach the diagnosis, query choice becomes important. In this work, 3 query ranking strategies in probabilistic expert systems are proposed and their performances on synthetic data are evaluated.
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