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Beschreibung
This book presents an overview of recent methods of feature selection and dimensionality reduction that are based on Deep Neural Networks (DNNs) for a clustering perspective, with particular attention to the knowledge discovery question. The authors first present a synthesis of the major recent influencing techniques and "tricks" participating in recent advances in deep clustering, as well as a recall of the main deep learning architectures. Secondly, the book highlights the most popular works by “family” to provide a more suitable starting point from which to develop a full understanding of the domain. Overall, the book proposes a comprehensive up-to-date review of deep feature selection and deep clustering methods with particular attention to the knowledge discovery question and under a multi-criteria analysis. The book can be very helpful for young researchers, non-experts, and R&D AI engineers.
Details
| Verlag | Springer International Publishing |
| Ersterscheinung | 04. Januar 2025 |
| Maße | 23.5 cm x 15.5 cm |
| Gewicht | 429 Gramm |
| Format | Softcover |
| ISBN-13 | 9783031487453 |
| Seiten | 268 |
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