polyview: A Python package for multi-view machine learning

Abstract:Multi-view learning jointly exploits multiple complementary representations of the same data and has become increasingly important in machine learning. However, the Python ecosystem lacks actively maintained, unified tooling for end-to-end multi-view workflows. In this paper, we present polyview, a Python package that provides tools for multi-view embedding, clustering, fusion, and view augmentation, as well as for handling incomplete views, all compatible with scikit-learn. The library offers a unified interface for composing heterogeneous multi-view workflows, including seamless transitions between multi-view and single-view stages. It is built around a core set of classes and utilities that enable composition of different methods and straightforward implementation of new ones. We illustrate the package on five real multi-view datasets and compare its components based on canonical correlation analysis with those of two established libraries. polyview aims to be both a practical toolkit for benchmarking and prototyping multi-view methods and a foundation for future research and development in this area.

Artificial Intelligence (cs.AI)

arXiv:2610.06491 [cs.AI]

(or arXiv:2610.06491v1 [cs.AI] for this version)

https://doi.org/10.48550/arXiv.2610.06491 Focus to learn more arXiv-issued DOI via DataCite (pending registration)

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