https://github.com/jatin-mehra119/insurance_dataset

The objective of this project is to predict insurance charges based on various factors.
https://github.com/jatin-mehra119/insurance_dataset

data-visualization dataanalysis prediction-model python regression-models

Last synced: 1 day ago
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The objective of this project is to predict insurance charges based on various factors.

• Host: GitHub
• URL: https://github.com/jatin-mehra119/insurance_dataset
• Owner: Jatin-Mehra119
• Created: 2024-05-27T17:19:12.000Z (6 months ago)
• Default Branch: main
• Last Pushed: 2024-05-27T18:02:32.000Z (6 months ago)
• Last Synced: 2024-05-28T04:45:28.874Z (6 months ago)
• Topics: data-visualization, dataanalysis, prediction-model, python, regression-models
• Language: Jupyter Notebook
• Homepage:
• Size: 3.07 MB
• Stars: 0
• Watchers: 1
• Forks: 0
• Open Issues: 0
• Metadata Files:
  • Readme: README.md

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README

        
# Insurance Charges Prediction

## Objective

The objective of this project is to predict insurance charges based on various factors such as age, sex, BMI, number of children, smoking status, and region. 

We will use machine learning techniques to build a predictive model that can estimate insurance charges given these inputs.

## Dataset

### The dataset used for this project consists of 1338 entries with the following columns:

1. **age**: Age of the primary beneficiary

2. **sex**: Gender of the primary beneficiary (male/female)

3. **bmi**: Body mass index, providing an understanding of body fat based on height and weight

4. **children**: Number of children/dependents covered by the insurance

5. **smoker**: Smoking status of the primary beneficiary (yes/no)

6. **region**: Residential area of the beneficiary in the US (northeast, southeast, southwest, northwest)

7. **charges**: Individual medical costs billed by health insurance