Ensemble Deep Learning for Biomedical Time Series Classification
文献类型：期刊论文
| 作者 | Jin, LP(金林鹏); Dong, J(董军) |
| 刊名 | COMPUTATIONAL INTELLIGENCE AND NEUROSCIENCE
 |
| 出版日期 | 2016 |
| 通讯作者 | Dong, J(董军) |
| 英文摘要 | Ensemble learning has been proved to improve the generalization ability effectively in both theory and practice. In this paper, we briefly outline the current status of research on it first. Then, a new deep neural network-based ensemble method that integrates filtering views, local views, distorted views, explicit training, implicit training, subview prediction, and Simple Average is proposed for biomedical time series classification. Finally, we validate its effectiveness on the Chinese Cardiovascular Disease Database containing a large number of electrocardiogram recordings. The experimental results show that the proposed method has certain advantages compared to some well-known ensemble methods, such as Bagging and AdaBoost. |
| 关键词[WOS] | NEURAL-NETWORK ENSEMBLES ; CLASSIFIERS ; ERROR ; RECOGNITION ; ALGORITHMS ; FORESTS |
| 收录类别 | SCI |
| 语种 | 英语 |
| WOS记录号 | WOS:000385079300001 |
| 源URL | [http://ir.sinano.ac.cn/handle/332007/4829]  |
| 专题 | 苏州纳米技术与纳米仿生研究所_学科交叉综合研究部_董军团队 |
| 推荐引用方式 GB/T 7714 | Jin, LP,Dong, J. Ensemble Deep Learning for Biomedical Time Series Classification[J]. COMPUTATIONAL INTELLIGENCE AND NEUROSCIENCE,2016. |
| APA | Jin, LP,&Dong, J.(2016).Ensemble Deep Learning for Biomedical Time Series Classification.COMPUTATIONAL INTELLIGENCE AND NEUROSCIENCE. |
| MLA | Jin, LP,et al."Ensemble Deep Learning for Biomedical Time Series Classification".COMPUTATIONAL INTELLIGENCE AND NEUROSCIENCE (2016). |
入库方式： OAI收割
浏览0
下载0
收藏0
其他版本
除非特别说明，本系统中所有内容都受版权保护，并保留所有权利。