2015大课程qwe数据分析

思考Wall猜测流失率和客户生命周期有关，是否正确？估计编号672，354和5203的客户的流失概率？他们属于需要重点关注的对象么？列出前20个最可能流失的客户，以及影响他们流失率的主要因素1QWE数据分析张诚复旦大学管理学院

3Logit/Logistic回归分析事件发生概率哪些因素导致手术后有的病人感染，有的不感染？哪些因素会让有的客户流失，有的客户不流失？流失概率Customer672：0.038104483Customer354：0.047797695Customer5203：0.042739255平均流失概率：0.05089018445整体Age1(0-5)Age2(6-14)Age3(>14)Customer_Age_inmonths0.012706CHI_M0-0.004660.001123-0.00886-0.01143CHI_M01-0.01027-0.02391-0.00318-0.00036Support_M0-0.15237-0.22895-0.17471-0.09098Support_M010.1702630.2794510.1415850.088144Blog_M010.000291-0.00215-0.049580.011825Views_M01-0.000114.41E-05-0.00015-0.00011DaysLastLogin_M010.0172420.0664980.0169830.000723sp_M00.0159290.517629-0.22838-0.01085sp_M01-0.05194-0.33580.0587250.017696Logins_M010.0002890.006835-0.00111-0.00303constant-2.76267-4.27492-1.68861-1.66152最易流失的前20位用户6ID分段估计9290.5097223570.43573847400.2868233350.26832436710.26193642920.25879537660.24577433200.2440679910.24295236040.24093641110.2396331630.2392432790.238532350.238540270.238532650.23841737340.2384175510.2383935260.2383945940.23839ID整体估计22870.3964653570.3501861090.30042519710.24712320760.21620720250.21529410.20151760.1935759290.19335813630.1905082990.188961287018726519290.183812140180274180.17812130.17808921017438478可否进一步分析影响每个用户流失的主要因素？策略1：寻找整体显著因素中该用户行为变化最大的变量策略2：寻找乘上系数后该用户行为变化最大的变量9与岱易的结果比较Churn\Pred0100.9314409030.06855909710.6532507740.346749226岱易的预测准确率：0.9016858老师的预测准确率：0.659366Churn\Pred0100.6570385130.34296148710.297213