OptImpute Documentation

OptImpute provides many learners for imputation of missing data. This documentation includes:

• a quick demo of imputation in action in the quick start guide
• a guide to the available imputation algorithms and their parameters
• recommended strategies for parameter tuning and selection
• a collection of tips and tricks for getting the best imputation results
• the OptImpute API reference

Citing OptImpute

If you use OptImpute in your work, we kindly ask that you cite the Interpretable AI software modules. We also ask that you reference the original paper that first introduced the algorithm:

@article{bertsimas2017predictive,
  title={From predictive methods to missing data imputation: an optimization approach},
  author={Bertsimas, Dimitris and Pawlowski, Colin and Zhuo, Ying Daisy},
  journal={The Journal of Machine Learning Research},
  volume={18},
  number={1},
  pages={7133--7171},
  year={2017},
  publisher={JMLR. org}
}