
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...
Editore
Springer Nature
Formato
512 pagine
ISBN
9783031015489
Lingua
English
Caratteristiche
A colori, 512 pagine
Genres
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