Logistic Regression for Insurance Prediction

This project applies Logistic Regression to predict whether a person will buy insurance based on their age.

Dataset

The dataset used in this project is insurance_data.csv, which contains:

• age: The age of the person
• bought_insurance: (0 or 1) indicating whether insurance was purchased

Dependencies

Ensure you have the following libraries installed:

pip install pandas numpy matplotlib scikit-learn

How to Run

1. Clone the repository (if applicable) or download the Untitled5.ipynb file.
2. Open Jupyter Notebook and navigate to the file.
3. Execute the cells sequentially.

Steps in the Notebook

1. Import necessary libraries.
2. Load and explore the dataset.
3. Visualize the data using scatter plots.
4. Split the data into training and test sets.
5. Train a Logistic Regression model using sklearn.
6. Make predictions and evaluate the model.

Results

The model predicts whether a person is likely to purchase insurance based on their age, using logistic regression.

Author

• Your Name (Replace with your actual name)

License

This project is for educational purposes only.