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arXiv · 2311.13695

BackboneLearn: A Library for Scaling Mixed-Integer Optimization-Based Machine Learning

Vassilis Digalakis Jr·Christos Ziakas
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Abstract

We present BackboneLearn: an open-source software package and framework for scaling mixed-integer optimization (MIO) problems with indicator variables to high-dimensional problems. This optimization paradigm can naturally be used to formulate fundamental problems in interpretable supervised learning (e.g., sparse regression and decision trees), in unsupervised learning (e.g., clustering), and beyond; BackboneLearn solves the aforementioned problems faster than exact methods and with higher accuracy than commonly used heuristics. The package is built in Python and is user-friendly and easily extensible: users can directly implement a backbone algorithm for their MIO problem at hand. The source code of BackboneLearn is available on GitHub (link: https://github.com/chziakas/backbone_learn).

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BibTeXRIS

Vassilis Digalakis Jr, Christos Ziakas. 2023-11-22. BackboneLearn: A Library for Scaling Mixed-Integer Optimization-Based Machine Learning. https://arxiv.org/abs/2311.13695

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