图 书 馆
标签容忍噪音的隐马尔可夫模型的分割为两个部分：应用ecgsLabel Noise-Tolerant Hidden Markov Models for Segmentation: Application to ECGs |
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| 课程网址: | http://videolectures.net/ecmlpkdd2011_frenay_ecgs/ |
| 主讲教师: | Benoît Frénay |
| 开课单位: | 天主教鲁汶大学 |
| 开课时间: | 2011-11-30 |
| 课程语种: | 英语 |
| 中文简介: |  |
| 课程简介: | The performance of traditional classification models can adversely be impacted by the presence of label noise in training observations. The pioneer work of Lawrence and Schölkopf tackled this issue in datasets with independent observations by incorporating a statistical noise model within the inference algorithm. In this paper, the specific case of label noise in non-independent observations is rather considered. For this purpose, a label noise-tolerant expectation-maximisation algorithm is proposed in the frame of hidden Markov models. Experiments are carried on both healthy and pathological electrocardiogram signals with distinct types of additional artificial label noise. Results show that the proposed label noise-tolerant inference algorithm can improve the segmentation performances in the presence of label noise. |
| 关 键 词: | 噪声统计模型; 马尔可夫模型; 心电图信号 |
| 课程来源: | 视频讲座网 |
| 最后编审: | 2019-11-28：lxf |
| 阅读次数: | 73 |