基于广义归纳逻辑因果模型的知识发现与算法实现

Algorithm and Realization of KDD Based on the Generalized Inductive Logical Causal Model

  • 摘要: 以语言场、广义细胞自动机和广义归纳逻辑因果模型为理论依据,分析了广义因果联系类知识的发现机理,给出了因果联系类知识发现的实现算法.该算法为解决具有随机不确定和模糊不确定性特征的因果联系类知识的发现提供了行之有效的方法.通过算法的运行实例,验证和说明了算法的正确性和有效性.

     

    Abstract: Based on the fuzzy language field, generalized cell automation and generalized inductive logical causal model, the mechanism of causal relation knowledge discovery were studied, and an algorithm of KDD with causal rules was proposed. With this algorithm, the causal relation knowledge discovery with uncertainty of random and fuzzy can be done effectively. An example illustrate the correctness and effectiveness of the algorithm.

     

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