  In this paper, we introduce eipy--an open-source Python package for
developing effective, multi-modal heterogeneous ensembles for classification.
eipy simultaneously provides both a rigorous, and user-friendly framework for
comparing and selecting the best-performing multi-modal data integration and
predictive modeling methods by systematically evaluating their performance
using nested cross-validation. The package is designed to leverage
scikit-learn-like estimators as components to build multi-modal predictive
models. An up-to-date user guide, including API reference and tutorials, for
eipy is maintained at https://eipy.readthedocs.io . The main repository for
this project can be found on GitHub at https://github.com/GauravPandeyLab/eipy .
