
Semi-supervised learning is a learning paradigm concerned with the study of how computers and natural systems such as humans learn in the presence of both labeled and unlabeled data. Traditionally, learning has been studied either in the unsupervised paradigm (e.g., clustering, outlier detection) where all the data is unlabeled, or in the supervised paradigm (e.g., classification, regression) wher...
Verlag
Springer Nature
Format
512 Seiten
ISBN
9783031015489
Sprache
English
Merkmale
Vollfarbig, 512 Seiten
Genres
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