A new predication method of customer credit of Banks is proposed based on the support vector domain classification model of non-balance data set.
基于非平衡数据集的支持向量域分类模型，提出了一种银行客户个人信用预测方法。
This thesis applies data mining techniques to customer segmentation based on customer value matrix and builds the classification model of customer with different value.
本文把数据挖掘技术应用于基于客户价值矩阵的客户价值细分中，建立各类价值客户的分类模型。
The paper discussed a model of customer classification based on Fuzzy ISODATA in CRM system.
探讨了在CRM系统中，基于模糊ISODATA的客户分类模型。
The result of examination indicates that this algorithm promote the capability of the customer churn prediction model, it's surely a successful application of link based classification.
实验结果表明，此算法较传统分类算法能提高客户流失预测性能，实现了基于链接分类方法的成功应用。
In this example, according to the loan, the numbers of loaning and the payment-in-time ratio, a model worked for classification of customer credit-rating is created.
然后，针对银行业务中客户信用政策给出了实例分析，用该算法建立了一个分类模型，根据存款金额、贷款次数、及时还贷率等数据信息实现对客户信用等级的分类。
In this example, according to the loan, the numbers of loaning and the payment-in-time ratio, a model worked for classification of customer credit-rating is created.
然后，针对银行业务中客户信用政策给出了实例分析，用该算法建立了一个分类模型，根据存款金额、贷款次数、及时还贷率等数据信息实现对客户信用等级的分类。
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