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Marketing Audit Value Model Based on Rough Set and Support Vector Regression Machine

机译:基于粗糙集的营销审计价值模型及支持向量回归机

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摘要

This study applies a new model based on rough set and support vector regression machine to enterprises' marketing audit value. To improve the efficiency, rough set was used to reduce the number of indexes. To improve the precision, the support vector regression machine was used. Then, the marketing audit value data of several companies were analyzed and 21 main indexes of marketing audit value were used. The experimental results demonstrate that the new method based on rough set and support vector regression machine has better precision than artificial neural network method and is more efficient than pure support vector regression machine method
机译:本研究适用于基于粗糙集和支持向量回归机的新模型,以企业的营销审计价值。为了提高效率,粗糙集用于减少指标的数量。为了提高精度,使用支持向量回归机器。然后,分析了几家公司的营销审计价值数据,并使用了21个主要营销审计价值指标。实验结果表明,基于粗糙集和支持向量回归机的新方法具有比人工神经网络方法更好的精度,比纯支持向量回归机方法更有效

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