SOL: A Library for Scalable Online Learning Algorithms [article]

Yue Wu, Steven C.H. Hoi, Chenghao Liu, Jing Lu, Doyen Sahoo, Nenghai Yu
2016 arXiv   pre-print
SOL is an open-source library for scalable online learning algorithms, and is particularly suitable for learning with high-dimensional data. The library provides a family of regular and sparse online learning algorithms for large-scale binary and multi-class classification tasks with high efficiency, scalability, portability, and extensibility. SOL was implemented in C++, and provided with a collection of easy-to-use command-line tools, python wrappers and library calls for users and
more » ... as well as comprehensive documents for both beginners and advanced users. SOL is not only a practical 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 machine learning with high-dimensional data.
arXiv:1610.09083v1 fatcat:hvyyzykaijb4tkwhvc6k3th7ra