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中文摘要：
目前，数据挖掘技术广泛应用于各个领域中。文中将数据挖掘应用于保险客户在信用等级的分类中，即采用了基于神经网络的覆盖算法作为客户信用评分分类器的设计算法。通过对保险数据的分析，对保险用户信用等级进行分类，降低了人为因素的评价干扰。通过分类实验表明，覆盖算法的准确性和网络训练速度都大大高于SVM。为保险公司有针对性的调查提供了一定的参考依据。
英文摘要：
Recently,data mining technology is widely applied in many fields. In this paper,data mining is applied to the credit sorting of insurance client,which used the coveting algorithm on which based neural networks as the classification of clients＇ credit. By analyzing the insurance data set, the algorithm sort the dients＇ credit, man- made disturbances are greatly eliminated. The experiment showed that the accuracy and speed of the covering algorithm is better than that of SVM. Then, it provides certain consultation for insurance company on farther investigating.
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