Multiview Machine Learning for Data Analysis
| Author/creator | Sun, Shiliang Author |
| Other author | Mao, Liang Author |
| Other author | Dong, Ziang Author |
| Other author | Wu, Lidan Author |
| Format | Electronic |
| Publication Info | New York : Springer Berlin : Springer [Distributor] Berlin : Springer [Distributor] |
| Description | x, 149 p. ill 23.500 x 015.500 cm. |
| Supplemental Content | Full text available from Springer Books |
| Supplemental Content | Full text available from Springer Nature - Springer Computer Science eBooks 2019 English International |
| Summary | Annotation <p>This book provides a unique, in-depth discussion of multiview learning, one of the fastest developing branches in machine learning. Multiview Learning has been proved to have good theoretical underpinnings and great practical success. This book describes the models and algorithms of multiview learning in real data analysis. Incorporating multiple views to improve the generalization performance, multiview learning is also known as data fusion or data integration from multiple feature sets. This self-contained book is applicable for multi-modal learning research, and requires minimal prior knowledge of the basic concepts in the field. It is also a valuable reference resource for researchers working in the field of machine learning and also those in various application domains. <br></p> |
| Access restriction | Available only to authorized users. |
| Technical details | Mode of access: World Wide Web |
| Genre/form | Electronic books. |
| ISBN | 9789811330285 |
| ISBN | 981133028X (Trade Cloth) Active Record |
| Standard identifier# | 9789811330285 |
| Stock number | 978-981-13-3028-5 00024965 |
Availability
| Library | Location | Call Number | Status | Item Actions |
|---|---|---|---|---|
| Electronic Resources | Access Content Online | ✔ Available |