insurance | R Documentation |
The insurance dataset contains 7 features and 1338 records. The target feature is charge and the remaining 6 variables are predictors.
data( insurance )
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.
A detailed description of the dataset can be found: https://www.kaggle.com/mirichoi0218/insurance
Brett Lantz (2019). Machine Learning with R: Expert techniques for predictive modeling. Packt Publishing Ltd.
adult
, risk
, churn
, churnTel
, bank
, advertising
, marketing
, cereal
, housePrice
, house
data( insurance ) str( insurance )
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