R: Customer Churn Data

churn {C50} | R Documentation

## Customer Churn Data

### Description

A data set from the MLC++ machine learning software for modeling customer churn. There are 19 predictors, mostly numeric: `state` (categorical), `account_length` `area_code` `international_plan` (yes/no), `voice_mail_plan` (yes/no), `number_vmail_messages` `total_day_minutes` `total_day_calls` `total_day_charge` `total_eve_minutes` `total_eve_calls` `total_eve_charge` `total_night_minutes` `total_night_calls` `total_night_charge` `total_intl_minutes` `total_intl_calls` `total_intl_charge`, and `number_customer_service_calls`.

### Details

The outcome is contained in a column called `churn` (also yes/no).

The training data has 3333 samples and the test set contains 1667.

A note in one of the source files states that the data are "artificial based on claims similar to real world".

A rule-based model shown on the RuleQuest website contains 19 rules, including:

    Rule 1: (60, lift 6.8)
             international_plan = yes
             total_intl_calls <= 2
             ->  class yes  [0.984]

    Rule 5: (43/2, lift 6.4)
            international_plan = no
            voice_mail_plan = no
            total_day_minutes > 246.6
            total_eve_charge > 20.5
            ->  class yes  [0.933]

    Rule 10: (211/84, lift 4.1)
             total_day_minutes > 264.4
              ->  class yes  [0.601]

### Value

`churnTrain` | The training set
`churnTest` | The test set.

### Source

http://www.sgi.com/tech/mlc/, http://www.rulequest.com/see5-examples.html

[Package C50 version 0.1.2 Index]