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Application of Decision Tree Algorithm in Lumber Hierarchies

机译:决策树算法在木材层次结构中的应用

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The decision tree algorithm is a kind of approximate discrete function value method with high precision, construction model of classification of noise data is simple and has good robustness etc, it is currently the most widely used in one of the inductive reasoning algorithms in data mining, extensive attention by researchers. This paper selects the decision tree ID3 algorithm to realize the standardization of lumber level division, to ensure the accuracy of the lumber division, while improving the partition of speed.
机译:决策树算法是一种具有高精度的近似离散函数值方法,噪声数据分类的施工模型简单且具有良好的鲁棒性等,目前是最广泛应用于数据挖掘中的一个归纳推理算法中,研究人员广泛关注。本文选择了决策树ID3算法实现了木材级别的标准化,以确保木材划分的准确性,同时提高速度分区。

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