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Insurance Prediction 🩺🧾

Image by <a href="https://pixabay.com/users/fidsor-26066389/?utm_source=link-attribution&utm_medium=referral&utm_campaign=image&utm_content=7065113">Fakhruddin Memon</a> from <a href="https://pixabay.com//?utm_source=link-attribution&utm_medium=referral&utm_campaign=image&utm_content=7065113">Pixabay</a>

About Dataset

  • 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, 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
  • region: The beneficiary's residential area in the US, northeast, southeast, southwest, northwest.
  • charges: Individual medical costs billed by health insurance

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Medical cost dataset modeling for insurance predictions of patients

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