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Support vector machines, Decision Trees and Neural Networks for auditor selection

机译:支持向量机,决策树和神经网络用于审计师选择

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The selection of a proper auditor is driven by several factors. Here, we use three data mining classification techniques to predict the auditor choice. The methods used are Decision Trees, Neural Networks and Support Vector Machines. The developed models are compared in term of their performances. The wrapper feature selection technique is used for the Decision Tree model. Two models reveal that the level of debt is a factor that influences the auditor choice decision. This study has implications for auditors, investors, company decision makers and researchers.
机译:选择合适的审核员受多种因素的驱动。在这里,我们使用三种数据挖掘分类技术来预测审计师的选择。使用的方法是决策树,神经网络和支持向量机。比较已开发模型的性能。包装器特征选择技术用于决策树模型。两种模型表明,债务水平是影响审计师选择决定的因素。这项研究对审计师,投资者,公司决策者和研究人员有影响。

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