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Predicting health insurance cost from Morality data using Machine Learning techniques

License: BSD 3-Clause "New" or "Revised" License

Python 100.00%

predicting-health-insurance-cost's Introduction

##Can the cost of health insurance be estimated automatically?

####Background: Insurance company especially health insurance company need to analyze how a customer is disease prone. We will try to find the risk based on the customers data.

If the Health_Risk can be estimated accurately then insurance cost can be calculated using this formula.


Health Insurance Cost = Base Cost + α * Health Risk

####We try to investigate how accurately we can estimate the health risk of a person.

Data Preprocessing

Total records : 1.04 M Has disease and non disease records. Disease related records : 0.56 M No. of feature: 34

###Feature information:

####Median and Quartile of each features

####Outlier Detection Used Box-Whisker plot to detect outlier.

####Class Imbalance Has high class imbalance

###Classification We applied K-Nearest Neighbour, Random Forest, Neural Network and Support Vector Machine algorithms to classify the different health risk.

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