【摘要】 针对纺织行业客户流失问题建立了基于支持向量机的预测模型。基于该行业预测客户流失指标属性多、相关系数高的特点,首先采用主成分分析法从多指标属性中筛选出客户流失的主要因素,有效地降低了支持向量机的训练维度。通过实际纺织行业的客户数据集测试,与普通支持向量机及其他传统预测模型进行比较,验证该模型具有良好的推广能力以及更高的精确性。更多还原

【Abstract】 To deal with customer churn problem in textile industry,this paper set up prediction model based on support vector machine(SVM).Due to easily-correlated、multi-index of indicative attributes in churn data,adopted principal component analysis(PCA) to screen out the main factors from a great deal of indicative attributes in order to reduce the training dimension of SVM effectively.With the application and verification in real textile data set,the result demonstrates that this model has a better universal property with higher precision than others.更多还原