A new algorithm for the knowledge discovery based on statistic induction logic is proposed, and the validity of the method is verified by examples. The method is suitable for a large range of knowledge discovery applications in the studying of causal relation, uncertainty knowledge acquisition and principal factors analyzing. The language field description of the state space makes the algorithm robust in the adaptation with easier understandable results, which are isomotopy with natural language in the topologic space.
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