图 书 馆
密度水平集的特征选择Feature Selection for Density Level-Sets |
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| 课程网址: | http://videolectures.net/ecmlpkdd09_brefeld_fsdls/ |
| 主讲教师: | Ulf Brefeld |
| 开课单位: | 莱芬娜大学 |
| 开课时间: | 2009-10-20 |
| 课程语种: | 英语 |
| 中文简介: |  |
| 课程简介: | A frequent problem in density level-set estimation is the choice of the right features that give rise to compact and concise representations of the observed data. We present an efficient feature selection method for density level-set estimation where optimal kernel mixing coefficients and model parameters are determined simultaneously. Our approach generalizes one-class support vector machines and can be equivalently expressed as a semi-infinite linear program that can be solved with interleaved cutting plane algorithms. The experimental evaluation of the new method on network intrusion detection and object recognition tasks demonstrate that our approach not only attains competitive performance but also spares practitioners from a priori decisions on feature sets to be used. |
| 关 键 词: | 密度水平集; 最佳核混合系数; 模型参数 |
| 课程来源: | 视频讲座网 |
| 最后编审: | 2019-03-24：cwx |
| 阅读次数: | 64 |