Construct · 1 fields · 1 citations

semi-supervised learning: a standalone construct

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Machine learning

learning from a small set of labeled data together with a larger set of unlabeled data, relying on assumptions such as smoothness, clustering or manifold structure.

In machine learning, semi-supervised learning refers to learning from a small set of labeled data together with a larger set of unlabeled data, relying on assumptions such as smoothness, clustering or manifold structure. This meaning comes from van Engelen (2019) in Machine Learning.[1]

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Nearby constructs

labeling3 fields · 5 citationsjingle · one word, three constructs learning6 fields · 14 citationsjingle · one name, six constructs manifold2 fields · 2 citationsjingle · one word, two constructs

References

van Engelen, J. E., & Hoos, H. H. (2019). A survey on semi-supervised learning. Machine Learning, 109(2), 373-440. https://doi.org/10.1007/s10994-019-05855-6

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