Transcription of A survey on semi-supervised learning - Springer
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Machine learning (2020) 109:373 440 survey on semi-supervised learningJesper E. van Engelen1 Holger H. Hoos1,2 Received: 3 December 2018 / Revised: 20 September 2019 / Accepted: 29 September 2019 /Published online: 15 November 2019 The Author(s) 2019 AbstractSemi- supervised learning is the branch of machine learning concerned with using labelledas well as unlabelled data to perform certain learning tasks. Conceptually situated betweensupervised and unsupervised learning , it permits harnessing the large amounts of unlabelleddata available in many use cases in combination with typically smaller sets of labelled recent years, research in this area has followed the general trends observed in machinelearning, with much attention directed at neural network-based models and generative learn-ing.
Semi-supervised learning is the branch of machine learning concerned with using labelled as well as unlabelled data to perform certain learning tasks. Conceptually situated between supervised and unsupervised learning, it permits harnessing the large amounts of unlabelled
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