insurance: insurance data set

In liver: "Eating the Liver of Data Science"

insurance data set

Description

the insurance dataset contains 7 features and 1338 records. the target feature is charge and the remaining 6 variables are predictors.

Usage

 data(insurance) 

Format

the insurance dataset, as a data frame, contains 1338 rows (customers) and 7 columns (variables/features). the 7 variables are:

• age: age of primary beneficiary.

• bmi: body mass index, providing an understanding of body, weights that are relatively high or low relative to height, objective index of body weight (kg / m ^ 2) using the ratio of height to weight, ideally 18.5 to 24.9.

• children: Number of children covered by health insurance / Number of dependents.

• smoker: Smoking as a factor with 2 levels, yes, no.

• gender: insurance contractor gender, female, male.

• region: the beneficiary's residential area in the US, northeast, southeast, southwest, northwest.

• charge: individual medical costs billed by health insurance.

Details

A detailed description of the dataset can be found:

https://www.kaggle.com/mirichoi0218/insurance

References

Brett Lantz (2019). Machine Learning with R: Expert techniques for predictive modeling. Packt Publishing Ltd.

See Also

adult, risk, churn, churnTel, bank, advertising, marketing, cereal, housePrice, house

Examples

data(insurance)

str(insurance)

liver documentation built on April 3, 2025, 10:51 p.m.