This project applies a machine learning ensemble model to predict the likelihood of stroke occurrences based on various health metrics. The dataset includes a range of health indicators and stroke occurrences for numerous patients.

The project has the following structure:

• Download the dataset from https://www.kaggle.com/datasets/fedesoriano/stroke-prediction-dataset and put it in data/
• healthcare-dataset-stroke-data.csv: The dataset containing health metrics and stroke occurrence for several patients.
• src/: Contains the source code for the project.
• stroke_prediction_classifier.py: The Python script that loads the data, trains the stroke prediction model, and evaluates its performance.
• predictions/: This directory contains the model's predictions on the test data.

To run the project, navigate to the 'src/' directory in your terminal or command prompt and execute the 'stroke_prediction_classifier.py' script. This will load the data, train the models, evaluate their performance, and save the predictions.

This project requires Python 3.6+ and several Python libraries which are listed in the requirements.txt file. Install them using:

pip install -r requirements.txt