图 书 馆
加权k出现对中心度感知分类方法的影响The influence of weighting the k-occurrences on hubness-aware classification methods |
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| 课程网址: | http://videolectures.net/sikdd2011_tomasev_hubness/ |
| 主讲教师: | Nenad Tomašev |
| 开课单位: | 约瑟夫·斯特凡学院 |
| 开课时间: | 2011-11-04 |
| 课程语种: | 英语 |
| 中文简介: |  |
| 课程简介: | Hubness is a phenomenon present in many highdimensional data sets. It is related to the skewness in the distribution of k-occurrences, i.e. occurrences of data points in k-neighbor sets of other data points. Several hubnessaware methods that focus on exploiting this phenomenon have recently been proposed. In this paper, we examine the potential impact of weighting the k-occurrences, by taking into account the distance between the respective data points, on hubness-aware nearest-neighbor methods, more specifically hw-kNN, h-FNN and HIKNN. We show that such distance-based weighting can be both advantageous and detrimental and that it influences different methods in different ways. |
| 关 键 词: | 中心度; 高维数据集中存在; 中心意识方法 |
| 课程来源: | 视频讲座网 |
| 最后编审: | 2020-06-03：liush |
| 阅读次数: | 46 |