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中文摘要：
客户特征提取是整个客户行为分析过程中的重要环节.由于客户特征提取时获得的数据具有多共同特征及大噪声等特点,使得在客户行为分析中进行客户特征提取存在较大误差.采用UCI机器学习数据库中有多个共同特征的数据集分别对典型特征提取算法进行实验对比及分类规则提取结果分析,验证了FC-GMDH算法在特征提取精度和抗干扰方面具有明显的优势,在客户行为分析时取得满意的特征提取效果.
英文摘要：
Customer feature extraction is an important part of the customer analysis. Because the data obtained from the customer feature extraction has many characteristics such as common features and large noise, so that there is a large error in the customer analysis of customer features extraction. The feature extraction and classification rule ex-traction experiment were done by using the UCI machine learning database respectively, and the experiments verified that the FC-GMDH algorithm has obvious advantages in feature extraction accuracy and anti-interference.
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