图 书 馆
成本敏感不确定性抽样的自训练方法A Self-Training Approach to Cost Sensitive Uncertainty Sampling |
|
| 课程网址: | http://videolectures.net/ecmlpkdd09_ghosh_asta/ |
| 主讲教师: | Joydeep Ghosh |
| 开课单位: | 德克萨斯大学 |
| 开课时间: | 2009-10-20 |
| 课程语种: | 英语 |
| 中文简介: |  |
| 课程简介: | Uncertainty sampling is an effective method for performing active learning that is computationally efficient compared to other active learning methods such as loss-reduction methods. However, unlike lossreduction methods, uncertainty sampling cannot minimize total misclassification costs when errors incur different costs. This paper introduces a method for performing cost-sensitive uncertainty sampling that makes use of self-training. We show that, even when misclassification costs are equal, this self-training approach results in faster reduction of loss as a function of number of points labeled and more reliable posterior probability estimates as compared to standard uncertainty sampling. We also show why other more naive methods of modifying uncertainty sampling to minimize total misclassification costs will not always work well. |
| 关 键 词: | 不确定性采样; 误判成本; 后验概率估计 |
| 课程来源: | 视频讲座网 |
| 最后编审: | 2020-06-08：yumf |
| 阅读次数: | 136 |