/Insurance-Fees

Machine Learning with R by Brett Lantz is a book that provides an introduction to machine learning using R. As far as I can tell, Packt Publishing does not make its datasets available online unless you buy the book and create a user account which can be a problem if you are checking the book out from the library or borrowing the book from a friend. All of these datasets are in the public domain but simply needed some cleaning up and recoding to match the format in the book. Content

Insurance

Context

Machine Learning with R by Brett Lantz is a book that provides an introduction to machine learning using R. As far as I can tell, Packt Publishing does not make its datasets available online unless you buy the book and create a user account which can be a problem if you are checking the book out from the library or borrowing the book from a friend. All of these datasets are in the public domain but simply needed some cleaning up and recoding to match the format in the book. Content

Columns

  • age: age of primary beneficiary
  • sex: insurance contractor gender, female, male
  • bmi: Body mass index, providing an understanding of body, weights that are relatively high or low relative to height,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
  • region: the beneficiary's residential area in the US, northeast, southeast, southwest, northwest.
  • charges: Individual medical costs billed by health insurance

Task

  • Which bmi had the cheapest insurance fees?
  • Which region had cheapest insurance fees?
  • Which ages had cheapest insurance fees?
  • Which sex pays the least amount of charges?
  • [BONUS] Predict the insurance fees of an individual.