Including the historical background and recent advances in the field as well as theoretical perspectives and real-world applications, this book outlines a systematic framework for implementing semi-supervised learning methods. It provides a toolbox on semi-supervised learning algorithms, presenting illustrations and examples of each algorithm. The book defines and distinguishes supervised learning, unsupervised learning, semi-supervised learning, and other relevant learning tasks. It discusses important semi-supervised learning models, including generative models for semi-supervised learning, semi-supervised support vector machines, and graph-based semi-supervised learning methods.
- ISBN10 1439826102
- ISBN13 9781439826102
- Publish Date 15 May 2017
- Publish Status Active
- Publish Country US
- Publisher Taylor & Francis Inc
- Imprint CRC Press Inc
- Format eBook
- Pages 250
- Language English