eipy: An Open-Source Python Package for Multi-modal Data Integration using Heterogeneous Ensembles
Abstract
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 .
Keywords
Cite
@article{arxiv.2401.09582,
title = {eipy: An Open-Source Python Package for Multi-modal Data Integration using Heterogeneous Ensembles},
author = {Jamie J. R. Bennett and Aviad Susman and Yan Chak Li and Gaurav Pandey},
journal= {arXiv preprint arXiv:2401.09582},
year = {2024}
}