This project aims to predict maternal mortality rates in Benin using a regression model. The model takes into account factors such as the number of sage femmes per 10,000 inhabitants, the number of hospitals, and whether the region has access to water.
The data used in this project includes information on the number of sage femmes per 10,000 inhabitants, the number of hospitals, and whether each region has access to water. This data was collected from various sources and preprocessed to prepare it for use in the machine learning model.
A regression model was used to predict maternal mortality rates in Benin. The model was trained on a dataset that included information on the number of sage femmes per 10,000 inhabitants, the number of hospitals, and whether each region has access to water. The performance of the model was evaluated using metrics such as mean squared error (MSE) and root mean squared error (RMSE).
To use this code, you will need to have Python and scikit-learn installed. You can install scikit-learn by running pip install scikit-learn in your terminal. Once you have the dependencies installed, you can run the code by navigating to the project directory and running python <filename>.py.
This code is licensed under the MIT license.