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SOL: A library for scalable online learning algorithms
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DOI：10.1016/j.neucom.2017.03.077.png)
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Abstract
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SOL is an open-source library for scalable online learning with high-dimensional data. The library provides a family of regular and sparse online learning algorithms for large-scale classification tasks with high efficiency, scalability, portability, and extensibility. We provide easy-to-use command-line tools, python wrappers and library calls for users and developers, and comprehensive documents for both beginners and advanced users. SOL is not only a machine learning toolbox, but also a comprehensive experimental platform for online learning research. Experiments demonstrate that SOL is highly efficient and scalable for large-scale learning with high-dimensional data. (C) 2017 Elsevier B.V. All rights reserved.
Keywords:
Online learning
Scalable machine learning
High dimensionality
Sparse learning
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