liver (version 1.5)

insurance: 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

# NOT RUN {
data( insurance )

str( insurance )
# }