churn_mlc: Churn data set from MLC++ machine learing

In liver: Toolkit and Datasets for Data Science

Churn data set from MLC++ machine learing

Description

This dataset originates from the MLC++ machine learning software and is used for modeling customer churn. Customer churn, also known as customer attrition, refers to the event in which customers stop doing business with a company. The dataset contains 5000 rows (customers) and 20 columns (features). The churn column serves as the target variable, indicating whether a customer has churned (left the company) or not.

Usage

data(churn_mlc)

Format

A data frame with 5000 rows (customers) and 20 columns (variables/features). the 20 variables are:

• state: Categorical, for the 51 states and the District of Columbia.

• area.code: Categorical.

• account.length: count, how long account has been active.

• voice.plan: Categorical, yes or no, voice mail plan.

• voice.messages: Count, number of voice mail messages.

• intl.plan: Categorical, yes or no, international plan.

• intl.mins: Continuous, minutes customer used service to make international calls.

• intl.calls: Count, total number of international calls.

• intl.charge: Continuous, total international charge.

• day.mins: Continuous, minutes customer used service during the day.

• day.calls: Count, total number of calls during the day.

• day.charge: Continuous, total charge during the day.

• eve.mins: Continuous, minutes customer used service during the evening.

• eve.calls: Count, total number of calls during the evening.

• eve.charge: Continuous, total charge during the evening.

• night.mins: Continuous, minutes customer used service during the night.

• night.calls: Count, total number of calls during the night.

• night.charge: Continuous, total charge during the night.

• customer.calls: Count, number of calls to customer service.

• churn: Categorical, yes or no. Indicator of whether the customer has left the company (yes or no).

Details

For more information related to the dataset see
- OpenML: https://www.openml.org/search?type=data&sort=runs&id=40701&status=active
- data.world: https://data.world/earino/churn

Source

This dataset is originally from http://www.sgi.com/tech/mlc

References

Saha, S., Saha, C., Haque, M. M., Alam, M. G. R., and Talukder, A. (2024). ChurnNet: Deep learning enhanced customer churn prediction in telecommunication industry. IEEE access, 12, 4471-4484.
Umayaparvathi, V., and Iyakutti, K. (2016). A survey on customer churn prediction in telecom industry: Datasets, methods and metrics. International Research Journal of Engineering and Technology (IRJET), 3(04), 1065-1070
Reza Mohammadi (2025). Data Science Foundations and Machine Learning with R: From Data to Decisions. https://book-data-science-r.netlify.app.

See Also

bank, churn, churn_tel, adult, risk, cereal, advertising, marketing, drug, house, house_price, red_wines, white_wines, insurance, caravan, fertilizer, corona

Examples

data(churn_mlc)
str(churn_mlc)

liver documentation built on Feb. 19, 2026, 1:07 a.m.