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Insurance companies are extremely interested in the prediction of the future. Accurate prediction gives a chance to reduce financial loss for the company. A major cause of increased costs are payment errors made by the insurance companies while processing claims. Furthermore, because of the payment errors, processing the claims again accounts

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PiyushRaj714/insurance-claim-prediction

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Insurance companies are extremely interested in the prediction of the future. Accurate prediction gives a chance to reduce financial loss for the company. A major cause of increased costs are payment errors made by the insurance companies while processing claims. Furthermore, because of the payment errors, processing the claims again accounts for a significant portion of administrative costs.

Dataset : This dataset contains 7 features as shown below:

age: age of the policyholder, sex: gender of policyholder (female=0, male=1), BMI: Body mass index, providing an understanding of the 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 25, steps: average walking steps per day of the policyholder, children: number of children/dependents of the policyholder, smoker: smoking state of policyholder (non-smoke=0;smoker=1), region: the residential area of the policyholder in the US (northeast=0, northwest=1, southeast=2, southwest=3), charges: individual medical costs billed by health insurance.

Installation Steps :- 1)Install Python 3.7.0 2)Install all dependencies cmd -python -m pip install –-user -r requirements.txt 3)Finally run cmd - python app.py

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Insurance companies are extremely interested in the prediction of the future. Accurate prediction gives a chance to reduce financial loss for the company. A major cause of increased costs are payment errors made by the insurance companies while processing claims. Furthermore, because of the payment errors, processing the claims again accounts

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