R语言电信公司churn数据客户流失 k近邻（knn）模型预测分析

Data background

A telephone company is interested in determining which customer characteristics are useful for predicting churn, customers who will leave their service.

The data set is Churn . The fields are as follows:

State	discrete.
account length	continuous.
area code	continuous.
phone number	discrete.
international plan	discrete.
voice mail plan	discrete.
number vmail messages	continuous.
total day minutes	continuous.
total day calls	continuous.
total day charge	continuous.
total eve minutes	continuous.
total eve calls	continuous.
total eve charge	continuous.
total night minutes	continuous.
total night calls	continuous.
total night charge	continuous.
total intl minutes	continuous.
total intl calls	continuous.
total intl charge	continuous.
number customer service calls	continuous.
churn	Discrete

Data Preparation and Exploration


查看数据概览
 
##      state      account.length    area.code        phone.number 
##  WV     : 158   Min.   :  1.0   Min.   :408.0    327-1058:   1  
##  MN     : 125   1st Qu.: 73.0   1st Qu.:408.0    327-1319:   1  
##  AL     : 124   Median :100.0   Median :415.0    327-2040:   1  
##  ID     : 119   Mean   :100.3   Mean   :436.9    327-2475:   1  
##  VA     : 118   3rd Qu.:127.0   3rd Qu.:415.0    327-3053:   1  
##  OH     : 116   Max.   :243.0   Max.   :510.0    327-3587:   1  
##  (Other):4240                                   (Other)  :4994  
##  international.plan voice.mail.plan number.vmail.messages
##   no :4527           no :3677       Min.   : 0.000       
##   yes: 473           yes:1323       1st Qu.: 0.000       
##                                     Median : 0.000       
##                                     Mean   : 7.755       
##                                     3rd Qu.:17.000       
##                                     Max.   :52.000       
##                                                          
##  total.day.minutes total.day.calls total.day.charge total.eve.minutes
##  Min.   :  0.0     Min.   :  0     Min.   : 0.00    Min.   :  0.0    
##  1st Qu.:143.7     1st Qu.: 87     1st Qu.:24.43    1st Qu.:166.4    
##  Median :180.1     Median :100     Median :30.62    Median :201.0    
##  Mean   :180.3     Mean   :100     Mean   :30.65    Mean   :200.6    
##  3rd Qu.:216.2     3rd Qu.:113     3rd Qu.:36.75    3rd Qu.:234.1    
##  Max.   :351.5     Max.   :165     Max.   :59.76    Max.   :363.7    
##                                                                      
##  total.eve.calls total.eve.charge total.night.minutes total.night.calls
##  Min.   :  0.0   Min.   : 0.00    Min.   :  0.0       Min.   :  0.00   
##  1st Qu.: 87.0   1st Qu.:14.14    1st Qu.:166.9       1st Qu.: 87.00   
##  Median :100.0   Median :17.09    Median :200.4       Median :100.00   
##  Mean   :100.2   Mean   :17.05    Mean   :200.4       Mean   : 99.92   
##  3rd Qu.:114.0   3rd Qu.:19.90    3rd Qu.:234.7       3rd Qu.:113.00   
##  Max.   :170.0   Max.   :30.91    Max.   :395.0       Max.   :175.00   
##                                                                        
##  total.night.charge total.intl.minutes total.intl.calls total.intl.charge
##  Min.   : 0.000     Min.   : 0.00      Min.   : 0.000   Min.   :0.000    
##  1st

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原文地址：https://blog.csdn.net/tecdat/article/details/127652987