CHAID算法精度性能分析

Chuancheng Deng, Feng Yi, Xing Li, Junyi Tang, Guang Sun
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引用次数: 0

摘要

决策树算法属于监督学习中的机器学习方法,是数据挖掘的常用技术之一。CHAID算法是一种常用的决策树算法。CHAID算法既可以用于预测,也可以用于分类。主要应用于市场分析、风险预测等领域。第二部分讲述了CHAID算法的核心思想和分类过程的具体步骤,以及CHAID算法主要使用的卡方检测的原理公式和具体的计算步骤。第三部分描述了CHAID算法与其他决策树算法的分支原理,并分析了CHAID算法的准确性。让我们根据具体的数据情况选择一个比较好的决策树算法,应用CHAID算法还可以根据一些影响准确率的因素做出一些对策,更有利于得到更准确更好的结果。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
Performance Analysis of CHAID Algorithm for Accuracy
Decision tree algorithm belongs to the machine learning method of supervised learning, and it is one of the common techniques of data mining. CHAID algorithm is one of the common decision tree algorithms. The CHAID algorithm can be used for prediction as well as for classification. It is mainly used in market analysis, risk prediction and other fields. The second part tells the core idea of CHAID algorithm and the specific steps of the classification process, as well as the principle formula of chi-square detection and the specific steps of the calculation mainly used by CHAID algorithm. The third part describes the branch principle of CHAID algorithm and other decision tree algorithm, and analyses the accuracy of CHAID algorithm. Let us choose a relatively good decision tree algorithm according to the specific data situation, and apply the CHAID algorithm can also make some countermeasures according to some factors affecting the accuracy, which is more conducive to get a more accurate and better result.
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