README.md
# Data imputation using Determinantal Point Process (DPP) - based methods
Please contact [Philip Teare](mailto:philip.teare@astrazeneca.com) with any questions about this repo.
This work presents an implementation of the models presented in the "[Improved clinical data imputation via classical and quantum determinantal point processes](https://arxiv.org/abs/2303.17893)" paper
## Prerequisites
Python 3.9
## Usage
```python
from models.imputers import DPPMissForest
ddpp_mf = DPPMissForest(batch_size=100, max_iter=5, n_estimators=10)
X_imputed = ddpp_mf.fit_transform(X_missing)
```
## License
[MIT](https://choosealicense.com/licenses/mit/)