SSLearn: A Semi-Supervised Learning library for Python']Python

被引:0
|
作者
Garrido-Labrador, Jose L. [1 ]
Maudes-Raedo, Jesus M. [1 ]
Rodriguez, Juan J. [1 ]
Garcia-Osorio, Cesar I. [1 ]
机构
[1] Univ Burgos, Escuela Politecn Super, Avd Cantabria S-N, Burgos 09006, Spain
关键词
Semi-supervised learning; !text type='Python']Python[!/text] library; Self-training; Co-training; Restricted set classification; SOFTWARE TOOL; ALGORITHMS; KEEL;
D O I
10.1016/j.softx.2024.102024
中图分类号
TP31 [计算机软件];
学科分类号
081202 ; 0835 ;
摘要
SSLearn is an open-source Python-based library that advances semi-supervised learning (SSL) with a focus on wrapper algorithms and restricted set classification (RSC), a novel paradigm. It fosters innovation by allowing researchers to modify methods or create new ones, facilitating access to state-of-the-art algorithms and comparative studies. As the only library incorporating RSC for constrained classification, SSLearn fills an important gap in SSL tools. Fully compatible with Scikit-Learn, it integrates seamlessly into research workflows, lowering the barrier to entry to SSL and catalyzing its adoption in diverse domains. This makes SSLearn a critical resource for advancing SSL research and applications.
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页数:7
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