出租房客户定位分析及电费回收策略

摘要

In the new situation of the"rental right", the num-ber of rental housing will usher in a new peak. Due to the difficuty to management of the floating population, there are often poor commu-nication of information, high arrears, high complaints, electricity in-stability, power security risks and other characteristics. In order to accurately locate the rental housing customers and with the service strategy, room customer electricity behavior,this paper uses the C5.0 decision tree algorithm applied to the rental housing to predict rental customers.%在"租售同权"的新形势下,出租房人数将迎来新高峰.由于对于流动人口难以管理,电力公司在回收出租房电费过程中常常存在信息沟通不畅、欠费高发、投诉纠纷高发、用电不稳定、用电安全隐患大等问题,为能准确定位出租房客户并采取相对应的电费回收服务策略,规范出租房客户用电行为,基于电力公司用户用电数据,运用大数据挖掘算法定位出租房用户.首先对出租房客户的基础信息、用电行为和缴费特征进行分析,根据分析结果提炼出对出租房分析影响较大的指标作为指标集,然后通过C5.0决策树算法进行机器自学习和训练,构建出租房用户判别模型.