Description Usage Format Source Examples
Predicting medical expenses
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A data frame with 1338 rows and 7 variables:
age
integer. age of primary beneficiary.
sex
character. insurance contractor gender, female, male.
bmi
double. 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
integer. Number of children covered by health insurance / Number of dependents.
smoker
character. Smoking (yes, no)
region
character. the beneficiary's residential area in the US, northeast, southeast, southwest, northwest.
charges
double. Individual medical costs billed by health insurance (in dollars).
From Machine Learning in R by Brett Lantz. Data downloaded from GitHub.
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