中文摘要：

为了解决客户细分中由于客户价值不同和不同价值客户数量的悬殊差异造成对客户错误分类的代价不同和不平衡的数据样本，研究了客户价值细分问题中错误分类代价形成机理，建立基于客户价值的动态代价函数，在此基础上设计了代价敏感的支持向量机分类器。实验结果说明，该方法可以更精确地控制代价敏感性，降低总体的错误分类代价，使模型能更准确地反映分类的代价，有效地识别客户价值。

英文摘要：

To reflect the influence caused by the great difference of misclassification costs and unbalanced quantity distribution of customers who have various values, the paper proposed the cost-sensitive SVM （support vector machine ） classifier by presenting misclassification cost function based on customer value, which was evaluated by the function of the exceptional lost. The data test result proves that the method can control the different types of errors distribution with various cost of misclassification accurately, reduce the total misclassification cost, and distinguish the customer value effectively.