Introduction to Semi-Supervised Learning

by Andrew Goldberg and Xiaojin Zhu

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. The goal of semi-supervised...

• Format: Paperback
• Language: English
• ISBN: 3031004205
• ISBN13: 9783031004209
• Release Date: June 2009
• Publisher: Springer
• Length: 116 Pages
• Weight: 0.53 lbs.
• Dimensions: 0.3" x 7.5" x 9.3"