【摘要】 针对目前电子商务中传统的对客户个人信用评价模式的不足,为提高泛化能力,提出一种以高斯核函数与支持向量机分类相结合的方法,构造出一种有效的客户个人信用评价模型。以某服装公司中客户作为实验数据,结果表明,该模型有比较好的泛化能力,在预测性能上明显优于现有的模型,能为电子商务中的信用评价体系提供有用的参考价值。更多还原

【Abstract】 Aiming at the deficiencies of traditional credit evaluation of personal customers in the current e-commerce,puts forward a combination of method of a Gaussian kernel with support vector machine classification method,which constructs an effective customer personal credit evaluation model to improve the generalization ability.Takes the clothing company customers data as the experimental data,and the result shows that the model is better than the existing models in credit evaluation model,which will provide a useful reference value for e-commerce in the credit evaluation system.更多还原