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A kind of classification and regression tree algorithm for unusual customers recognition in telecom trade

机译：一种用于电信交易中异常客户识别的分类回归树算法

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摘要

The recognition of unusual customers is one of the most important applications in data mining. Using an example from telecom trade, This work presents a kind of classification and regression tree algorithm to recognize unusual customers in telecommunication trade databases (TCART for short). The TCART includes the following process: maximal classification tree construction, regression pruning and optimal classification tree selection. During the procedure of classification tree growing, we propose improved classification approaches. Finally, the TCART algorithm is validated by large numbers of customer data in the Zhejiang telecom database. The experimental results indicate that the TCART algorithm has the virtues of robustness and effectiveness.

机译：对异常客户的认可是数据挖掘中最重要的应用之一。这项工作使用电信贸易的示例，提供了一种分类和回归树算法，可以识别电信交易数据库中的异常客户（TCART for Short）。 TCart包括以下过程：最大分类树施工，回归修剪和最佳分类树选择。在分类树的过程中，我们提出了改进的分类方法。最后，通过浙江电信数据库中的大量客户数据验证了TCart算法。实验结果表明，TCART算法具有鲁棒性和有效性的美德。

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来源
《》|2004年|p.561-564|共4页
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作者
Yao Min; Shen Bin; Li Ming-fang;
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正文语种
中图分类无线电电子学、电信技术;
关键词
data mining; decision trees; consumer behaviour; customer profiles; marketing data processing; very large databases; pattern classification; telecommunication services; regression analysis; regression tree algorithm; unusual customer recognition; regression pruning; optimal classification tree selection; Zhejiang telecom database; data mining; telecommunication trade databases; maximal classification tree construction;

机译：数据挖掘;决策树;消费者行为;客户概况;营销数据处理;大型数据库;模式分类;电信服务;回归分析;回归树算法;异常客户识别;回归修剪;最优分类树选择;浙江电信数据库;数据采矿;电信行业数据库;最大分类树构建;

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A kind of classification and regression tree algorithm for unusual customers recognition in telecom trade

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