CapyMOA: Efficient Machine Learning for Data Streams in Python

• URL: http://arxiv.org/abs/2502.07432v1
• Date: Tue, 11 Feb 2025 10:20:04 GMT
• Title: CapyMOA: Efficient Machine Learning for Data Streams in Python
• Authors: Heitor Murilo Gomes, Anton Lee, Nuwan Gunasekara, Yibin Sun, Guilherme Weigert Cassales, Justin Liu, Marco Heyden, Vitor Cerqueira, Maroua Bahri, Yun Sing Koh, Bernhard Pfahringer, Albert Bifet,
• Abstract summary: CapyMOA is an open-source library for efficient machine learning on streaming data.<n>CapyMOA includes an architecture that allows integration with external frameworks such as MOA and PyTorch.
• Score: 11.597798770955425
• License: http://creativecommons.org/licenses/by/4.0/
• Abstract: CapyMOA is an open-source library designed for efficient machine learning on streaming data. It provides a structured framework for real-time learning and evaluation, featuring a flexible data representation. CapyMOA includes an extensible architecture that allows integration with external frameworks such as MOA and PyTorch, facilitating hybrid learning approaches that combine traditional online algorithms with deep learning techniques. By emphasizing adaptability, scalability, and usability, CapyMOA allows researchers and practitioners to tackle dynamic learning challenges across various domains.

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