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A Multi-Model of Classification for Electric-Power Industrial Customer Based on Big Data

机译:基于大数据的电力工业客户分类模型

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Aiming to help Electric-Power Industry to fast recognize customer's features, a multi-model of customer classification is proposed in this paper. On basis of big data presented by CCF competition sponsor in China, with some excellent technology or algorithm such as JieBa, SFFS and so on, we extract many important features and successfully draw a portrait for customers who pay close attention to electricity charges. Furthermore, machine learning algorithm and its the strategy selection model are investigated. Eventually, a multi-model is achieved, which can effective draw customer portrait and recognize targeted customer from big data. The result of experiment indicate that the multi-model has precision of 84%, good recall and excellent generalization.
机译:为了帮助电力行业快速识别客户的特征,本文提出了一种客户分类的多模型。根据中国CCF竞赛赞助商提供的大数据,结合JieBa,SFFS等一些出色的技术或算法,我们提取了许多重要特征并成功为关注电费的客户绘制了肖像。此外,研究了机器学习算法及其策略选择模型。最终,实现了一个多模型,可以有效地绘制客户画像并从大数据中识别目标客户。实验结果表明,该模型具有84%的精度,良好的查全率和优良的泛化能力。

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