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Applying genetic programming technique in classification trees

机译:遗传程序设计技术在分类树中的应用

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Classification problems are often encountered in many applications. In the past, classification trees were often generated by decision-tree methods and commonly used to solve classification problems. In this paper, we have proposed an algorithm based on genetic programming to search for an appropriate classification tree according to some criteria. The classification tree obtained can be transferred into a rule set, which can then be fed into a knowledge base to support decision making and facilitate daily operations. Two new genetic operators, elimination and merge, are designed in the proposed approach to remove redundancy and subsumption, thus producing more accurate and concise decision rules than that without using them. Experimental results from the credit card data also show the feasibility of the proposed algorithm.
机译:在许多应用程序中经常遇到分类问题。过去,分类树通常是通过决策树方法生成的,通常用于解决分类问题。在本文中,我们提出了一种基于遗传规划的算法,可以根据一些准则搜索合适的分类树。可以将获得的分类树转移到规则集中,然后可以将其输入到知识库中以支持决策制定并促进日常操作。在提出的方法中设计了两个新的遗传算子,消除和合并,以消除冗余和包含,从而比不使用它们时产生更准确和简洁的决策规则。信用卡数据的实验结果也表明了该算法的可行性。

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