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Application of Data Mining Classification Algorithms in Customer Membership Card Classification Model

机译:数据挖掘分类算法在客户会员卡分类模型中的应用

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This paper uses data mining classification algorithms--^sC5.0 and CART algorithms to get useful information to decision-making out of customers’ transaction behaviors. Firstly, by business understanding, data understanding and data preparing, modeling and evaluating we get the results of the two algorithms and by comparing the results ,we know that the two algorithms can both be applied in the customer membership card classification model and can obtain a quite accurate result. Then we introduce the application of this model. Through analysis, we get to know customers’ income level and children number are the two main factors to affect them to choose cards. Knowing that, enterprises can take corresponding measures, such as dividing customers into different groups and then recommending the corresponding card to the customer who has the similar characteristics. By this means, enterprises can provide special service to different card rank users in order to attract more and more customers.
机译:本文使用数据挖掘分类算法 - ^ SC5.0和购物车算法,以获取有用的信息,以解决客户的交易行为的决策。首先,通过商业理解,数据理解和数据准备,建模和评估我们得到了两种算法的结果,通过比较结果,我们知道这两个算法都可以应用于客户成员资格卡分类模型,并可以获得一个结果非常准确。然后我们介绍了这个模型的应用程序。通过分析,我们了解客户的收入水平,儿童数量是影响他们选择卡片的两个主要因素。知道这一点,企业可以采取相应的措施,如将客户分成不同的群体,然后将相应的卡推荐给具有相似特征的客户。通过这种方式,企业可以为不同的卡等级用户提供特殊服务,以吸引越来越多的客户。

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