Cost-sensitive method for customer segmentation
客户价值细分的代价敏感支持向量机方法

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.