基于机器学习的猪场用户流失分析
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摘要
为实现养殖互联网平台用户的自动化运营,防止用户流失,采用区间估计和机器学习建模方法,对猪场用户的平台使用情况进行用户流失分析。结果表明:1)猪场规模越小,用户流失的概率越大,其中500<母猪数x≤1 000的猪场规模用户流失的概率最小,属于忠诚用户;2)使用决策树算法、kNN算法、贝叶斯分类算法进行猪场用户流失分析建模,3种分类算法中,从平均识别率(F_1度量)考虑,决策树模型的平均识别率(0.93)高于kNN模型(0.91)和贝叶斯分类模型(0.80),选择决策树算法用于平台用户流失分析建模是可行的。本研究所构建的猪场用户流失分析模型,可为养殖互联网平台的猪场用户研究提供可靠的数据模型,实现平台用户的自动化运营,也可为其他类型的用户研究和产品设计提供参考。
In order to realize the automatic operation of users and prevent user churn,interval estimation and machine learning modeling methods are adopted to analyze user churn by data records of pig farm users.The results show that:1) The smaller the pig farm is,the greater the possibility of user churn is.The least possible churn of pig farm users,whose number of sows x is at 500
In order to realize the automatic operation of users and prevent user churn,interval estimation and machine learning modeling methods are adopted to analyze user churn by data records of pig farm users.The results show that:1) The smaller the pig farm is,the greater the possibility of user churn is.The least possible churn of pig farm users,whose number of sows x is at 500
引文
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[2] 李海舰,田跃新,李文杰.互联网思维与传统企业再造[J].中国工业经济,2014(10):135-146Li H J,Tian Y X,Li W J.Mobile internet thinking and traditional business reengineering[J].China Industrial Economics,2014(10):135-146 (in Chinese)
[3] 郭顺利,张向先,相甍甍.高校图书馆微信公众平台用户流失行为模型及其影响因素分析[J].图书情报工作,2017,61(2):57-66 Guo S L,Zhang X X,Xiang M M.Research on the customer churn behavior model and its influencing factors of WeChat public platform in university libraries[J].Library and Information Service,2017,61 (2):57-66 (in Chinese)
[4] 谭莹.我国生猪生产效率及补贴政策评价[J].华南农业大学学报:社会科学版,2010,9(3):84-90Tan Y.Analysis on live pig production efficiency and live pig subsidy policy in China[J].Journal of South China Agricultural University:Social Science Edition,2010,9(3):84-90 (in Chinese)
[5] 徐孝娟,赵宇翔,朱庆华.社交网站用户流失行为理论基础及影响因素探究[J].图书情报工作,2016,60(4):134-141Xu X J,Zhao Y X,Zhu Q H.Theoretical basis and influence factors of user exodus behavior of social networking sites[J].Library and Information Service,2016,60(4):134-141 (in Chinese)
[6] 刘勇,万维新,康子轶.中国电信业流失客户分类研究[J].统计教育,2009(1):26-30Liu Y,Wan W X,Kang Z Y.Study on the lost customers classification of Chinese telecom industry[J].Statistical Education,2009(1):26-30 (in Chinese)
[7] 江积海,张烁亮.平台型商业模式创新中价值创造的属性动因及其作用机理[J].中国科技论坛,2015(7):154-160Jiang J H,Zhang S L.On the internal attributes and mechanism in value creation of platform-based business model innovation[J].Forum on Science and Technology in China,2015(7):154-160 (in Chinese)
[8] 徐孝娟,赵宇翔,朱庆华,孙霄凌.社交网站中用户流失要素的理论探讨及实证分析[J].信息系统学报,2013(2):83-97Xu X J,Zhao Y X,Zhu Q H,Sun X L.Theoretical discussion and empirical analysis of user loss factors in social networking sites[J].China Journal of Information Systems,2013(2):83-97 (in Chinese)
[9] 潘红英,郑卫兵,王德刚.猪群死亡分布规律分析及相关控制技术探讨[J].浙江农业科学,2005,46(3):221-223Pan H Y,Zheng W B,Wang D G.Analysis of distribution pattern of pig death and preventing approaches[J].Journal of Zhejiang Agricultural Sciences,2005,46(3):221-223 (in Chinese)
[10] 李倩,钟胜.面向管理改进的服务企业顾客满意度模型[J].商业经济与管理,2005(4):66-71Li Q,Zhong S.The customer satisfaction model for management improvement of service enterprises[J].Journal of Business Economics,2005(4):66-71 (in Chinese)
[11] 王永贵,董大海.客户关系管理的研究现状、不足和未来展望[J].中国流通经济,2004,18(6):52-56Wang Y G,Dong D H.Customer relationship management:Current situation,weakness and future research directions[J].China Business and Market,2004,18(6):52-56 (in Chinese)
[12] 严浩仁,贾生华.顾客忠诚的基本驱动模型研究:以移动通信服务为例[J].经济管理,2005(4):42-46Yan H R,Jia S H.Analysis on the basic drive model of customer loyalty:The case study of mobile communication service[J].Business Management Journal,2005(4):42-46 (in Chinese)
[13] 李震.互联网平台如何创造体验价值:基于互动视角的分析[J].广东财经大学学报,2017,32(2):15-30Li Z.How to create experiential value based on internet platform:An analysis from the perspective of interaction[J].Journal of Guangdong University of Finance & Economics,2017,32(2):15-30 (in Chinese)
[14] Spackman K A.Signal detection theory:Valuable tools for evaluating inductive learning[C].In:Proceedings of the sixth International Workshop on Machine Learning.San Francisco:Morgan Kaufmann Publishers Inc.,1989:160-163
[15] 卢元磊,何佳洲,安瑾,苗高洁.几种野值剔除准则在目标预测中的应用研究[J].指挥控制与仿真,2011,33(4):98-102Lu Y L,He J Z,An J,Miao G J.Research on rules for eliminating outliers and its application to target prediction[J].Command Control & Simulation,2011,33(4):98-102 (in Chinese)
[16] Zhang M L,Zhou Z H.A review on multi-label learning algorithms[J].IEEE Transactions on Knowledge and Data Engineering,2014,26(8):1819-1837
[17] Utgoff P E,Berkman N C,Clouse J A.Decision tree induction based on efficient tree restructuring[J].Machine Learning,1997,29(1):5-44
[18] 周志华.机器学习[M].北京:清华大学出版社,2016:73-74Zhou Z H.Machine Learning[M].Beijing:Tsinghua University Press,2016:73-74 (in Chinese)
[19] Weinberger K Q,Blitzer J,Saul L K.Distance metric learning for large margin nearest neighbor classification [J].Journal of Machine Learning Research,2009,10(1):207-244
[20] Domingos P,Pazzani M.On the optimality of the simple Bayesian classifier under zero-one loss[J].Machine Learning,1997,29(2-3):103-130
[21] Friedman N,Geiger D,Goldszmidt M.Bayesian network classifiers[J].Machine Learning,1997,29(2-3):131-163
[22] Grossman D,Domingos P.Learning Bayesian network classifiers by maximizing conditional likelihood[C].In:Proceedings of the 21th International Conference on Machine Learning 2004.New York:Association Computing Machinery,2004:361-368
[23] Bradley A P.The use of the area under the ROC curve in the evaluation of machine learning algorithms[J].Pattern Recognition,1997,30(7):1145-1159
[24] Fawcett T.An introduction to ROC analysis[J].Pattern Recognition Letters,2006,27(8):861-874
[25] Hand D J,Till R J.A simple generalisation of the area under the ROC curve for multiple class classification problems[J].Machine Learning,2001,45(2):171-186