Introduction to Semi-Supervised Learning by Xiaojin ZhuEnglish | PDF | 2009 | 130 Pages | ISBN : 1598295470 | 1.15 MB
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 are unlabeled, or in the supervised paradigm (e.g., classification, regression) where all the data are labeled.