A demo modeling Insurance data, individuals along with their policies, claims, and incidents. Using Memgraph, utilizes the power of graphs to model the data and detect fraudulent claims. Extracts features using graph algorithms and uses machine learning to evaluate insurance claims.
You can set up the project with poetry:
poetry install
Or, if you don't want to use poetry, simply:
pip install -r requirements.txt
The demo is located in ./fraud_detection_demo.ipynb.
Recommended Python version is 3.9, since sklearn package doesn't yet support Python 3.10.
If you want to just use the dataset, try running:
python dataset/data_generator.py 1000 300
And to import it into Memgraph, first start Memgraph, and then run the load script:
docker run -it -p 7687:7687 -p 3000:3000 memgraph/memgraph-platform
python load_demo_dataset.py