图 书 馆
高维数据中的最近邻：中心的出现和影响Nearest Neighbors in High-Dimensional Data: The Emergence and Influence of Hubs |
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| 课程网址: | https://videolectures.net/videos/icml09_radovanovic_nnh |
| 主讲教师: | Miloš Radovanović |
| 开课单位: | 会议 |
| 开课时间: | 2009-08-26 |
| 课程语种: | 英语 |
| 中文简介: |  |
| 课程简介: | High dimensionality can pose severe difficulties, widely recognized as different aspects of the curse of dimensionality. In this paper we study a new aspect of the curse pertaining to the distribution of k-occurrences, i.e., the number of times a point appears among the k nearest neighbors of other points in a data set. We show that, as dimensionality increases, this distribution becomes considerably skewed and hub points emerge (points with very high k-occurrences). We examine the origin of this phenomenon, showing that it is an inherent property of highdimensional vector space, and explore its influence on applications based on measuring distances in vector spaces, notably classification, clustering, and information retrieval. |
| 关 键 词: | 高维数据; 维度灾难; 数据集 |
| 课程来源: | 视频讲座网 |
| 数据采集: | 2025-04-25：liyq |
| 最后编审: | 2025-04-25：liyq |
| 阅读次数: | 6 |