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

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.