Awat A. Saeed

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—Semi-supervised learning involves constructing pre-dictive models with both labelled and unlabelled training data. The need for semi-supervised learning is driven by the fact that unlabelled data are often easy and cheap to obtain, whereas labelling data requires costly and time consuming human intervention and expertise. Semi-supervised methods commonly(More)
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