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Research and application of conditional probability decision tree algorithm in data mining

机译:条件概率决策树算法在数据挖掘中的研究与应用

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Decision tree algorithm is a very active research area of data mining. This paper describes the basic decision tree idea in data mining, then discusses the computational complexity of the classical decision tree algorithm (ID3 algorithm). And the improved algorithm to construct a decision tree by using statistical theory and ideas of conditional probability is proposed in this paper. Experiments show that the computational complexity of this decision tree algorithm is superior to the traditional algorithm, and its efficiency is greatly improved.
机译:决策树算法是数据挖掘的一个非常活跃的研究领域。本文介绍了数据挖掘中的基本决策树思想,然后讨论了经典决策树算法(ID3算法)的计算复杂性。提出了一种利用统计理论和条件概率思想构造决策树的改进算法。实验表明,该决策树算法的计算复杂度优于传统算法,效率大大提高。

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