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arXiv · 2512.01287

milearn: A Python Package for Multi-Instance Machine Learning

Dmitry Zankov·Pavlo Polishchuk·Michal Sobieraj·Mario Barbatti
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Abstract

We introduce milearn, a Python package for multi-instance learning (MIL) that follows the familiar scikit-learn fit/predict interface while providing a unified framework for both classical and neural-network-based MIL algorithms for regression and classification. The package also includes built-in hyperparameter optimization designed specifically for small MIL datasets, enabling robust model selection in data-scarce scenarios. We demonstrate the versatility of milearn across a broad range of synthetic MIL benchmark datasets, including digit classification and regression, molecular property prediction, and protein-protein interaction (PPI) prediction. Special emphasis is placed on the key instance detection (KID) problem, for which the package provides dedicated support.

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Dmitry Zankov, Pavlo Polishchuk, Michal Sobieraj, Mario Barbatti. 2025-12-01. milearn: A Python Package for Multi-Instance Machine Learning. https://arxiv.org/abs/2512.01287

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