| 書目名稱 | Principles of Nonparametric Learning |
| 編輯 | László Gy?rfi |
| 視頻video | http://file.papertrans.cn/756/755722/755722.mp4 |
| 叢書名稱 | CISM International Centre for Mechanical Sciences |
| 圖書封面 |  |
| 描述 | The book provides systematic in-depth analysis of nonparametric learning. It covers the theoretical limits and the asymptotical optimal algorithms and estimates, such as pattern recognition, nonparametric regression estimation, universal prediction, vector quantization, distribution and density estimation and genetic programming.The book is mainly addressed to postgraduates in engineering, mathematics, computer science, and researchers in universities and research institutions. |
| 出版日期 | Book 2002 |
| 關(guān)鍵詞 | Pattern Recognition; Probability and Statistics in Computer Science; Signal Processing; Statistical The |
| 版次 | 1 |
| doi | https://doi.org/10.1007/978-3-7091-2568-7 |
| isbn_softcover | 978-3-211-83688-0 |
| isbn_ebook | 978-3-7091-2568-7Series ISSN 0254-1971 Series E-ISSN 2309-3706 |
| issn_series | 0254-1971 |
| copyright | Springer-Verlag Wien 2002 |
|Archiver|手機版|小黑屋|
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