What Is Semi-Supervised Learning?
Semi-Supervised Learning is a machine-learning approach that trains on a small amount of labelled data together with a larger amount of unlabelled data.
Semi-Supervised Learning — a machine-learning approach that trains on a small amount of labelled data together with a larger amount of unlabelled data.
Semi-supervised learning is common where labelling is expensive but raw data is plentiful. It can improve performance over using labelled data alone, but it inherits the data-governance concerns of both approaches: the quality of the few labels and the representativeness of the much larger unlabelled set.
Source: ISO/IEC 22989:2022 (AI concepts and terminology)
Plain-language explanation
Semi-supervised learning is common where labelling is expensive but raw data is plentiful. It can improve performance over using labelled data alone, but it inherits the data-governance concerns of both approaches: the quality of the few labels and the representativeness of the much larger unlabelled set.
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