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LAMDA-SSL: a comprehensive semi-supervised learning toolkit
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DOI：10.1007/s11432-022-3804-0.png)
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Abstract
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In this study, we present an easy-to-use, powerful, and open-source toolkit in Python for SSL with comprehensive functionality, simple interfaces, complete documentation, and the best support for algorithms, data types, and tasks compared with related toolkits. Our aim is to facilitate SSL research and applications by addressing the challenge of limited labeled data. Going forward, we plan to incorporate advanced algorithms into LAMDA-SSL and expand its application scope in open environments [9].
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