Skip to content

In this Data set we are Predicting the Insurance Claim by each user, Machine Learning algorithms for Regression analysis are used and Data Visualization are also performed to support Analysis.

License

Notifications You must be signed in to change notification settings

hsheraz/Insurance-Claim-Prediction

 
 

Repository files navigation

Insurance-Claim-Prediction

In this Data set we are Predicting the Insurance Claim by each user, Machine Learning algorithms for Regression analysis are used and Data Visualization are also performed to support Analysis.

Content

This is "Sample Insurance Claim Prediction Dataset" which based on "[Medical Cost Personal Datasets][1]" to update sample value on top.

age :

age of policyholder 

sex:

gender of policy holder (female=0, male=1)

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 25 

steps:

average walking steps per day of policyholder 

children:

number of children / dependents of policyholder 

smoker:

smoking state of policyholder (non-smoke=0;smoker=1)

region:

the residential area of policyholder in the US (northeast=0, northwest=1, southeast=2, southwest=3) 

charges:

individual medical costs billed by health insurance

insuranceclaim:

yes=1, no=0

About

In this Data set we are Predicting the Insurance Claim by each user, Machine Learning algorithms for Regression analysis are used and Data Visualization are also performed to support Analysis.

Resources

License

Stars

Watchers

Forks

Releases

No releases published

Packages

No packages published

Languages

  • Jupyter Notebook 100.0%