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商品詳細
Advances in Feature Selection for Data and Pattern Recognition. 1st ed. 2018
・ISBN 978-3-319-67587-9 hard EUR 99.99
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お気に入り
★★★
| 著者・編者 | Stanczyk, Urszula / Zielosko, Beata / Jain, Lakhmi C. (eds.), |
|---|---|
| シリーズ | (Intelligent Systems Reference Library) |
| 出版社 | (Springer International Publishing AG, SZ) |
| 出版年月 | 2017 |
| ページ数 | 328 pp. |
| 言語 | ENG |
| ニュース番号 | ＜A02-62056＞ |
解説
This book presents recent developments and research trends in the field of feature selection for data and pattern recognition, highlighting a number of latest advances.
The field of feature selection is evolving constantly, providing numerous new algorithms, new solutions, and new applications. Some of the advances presented focus on theoretical approaches, introducing novel propositions highlighting and discussing properties of objects, and analysing the intricacies of processes and bounds on computational complexity, while others are dedicated to the specific requirements of application domains or the particularities of tasks waiting to be solved or improved.
Divided into four parts - nature and representation of data; ranking and exploration of features; image, shape, motion, and audio detection and recognition; decision support systems, it is of great interest to a large section of researchers including students, professorsand practitioners.
The field of feature selection is evolving constantly, providing numerous new algorithms, new solutions, and new applications. Some of the advances presented focus on theoretical approaches, introducing novel propositions highlighting and discussing properties of objects, and analysing the intricacies of processes and bounds on computational complexity, while others are dedicated to the specific requirements of application domains or the particularities of tasks waiting to be solved or improved.
Divided into four parts - nature and representation of data; ranking and exploration of features; image, shape, motion, and audio detection and recognition; decision support systems, it is of great interest to a large section of researchers including students, professorsand practitioners.