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Semi-supervised rotation forest
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DOI：10.1016/j.jocs.2025.102777.png)
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Abstract
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• A semi-supervised learning (SSL) variant of Rotation Forest (SSRotF) is proposed. • A comparison between the supervised Rotation Forest and SSRotF is presented. • An extensive experimentation (54 datasets and 12 label proportions) is conducted. • A meta-learning approach is investigated to identify datasets suitable for SSL.
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J
IF:
3.7
Papers:
244
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0
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