Multi layer ELM-RBF for multi-label learning
文献类型：期刊论文
| 作者 | Zhang, Nan1,2; Ding, Shifei1,2; Zhang, Jian1,2 |
| 刊名 | APPLIED SOFT COMPUTING
 |
| 出版日期 | 2016-06-01 |
| 卷号 | 43页码:535-545 |
| 关键词 | Multi-label learning Extreme learning machine Radial basis function k-Means clustering Extreme learning machine based auto encoder (ELM-AE) |
| ISSN号 | 1568-4946 |
| DOI | 10.1016/j.asoc.2016.02.039 |
| 英文摘要 | Many neural network methods such as ML-RBF and BP-MLL have been used for multi-label classification. Recently, extreme learning machine (ELM) is used as the basic elements to handle multi-label classification problem because of its fast training time. Extreme learning machine based auto encoder (ELM-AE) is a novel method of neural network which can reproduce the input signal as well as auto encoder, but it can not solve the over-fitting problem in neural networks elegantly. Introducing weight uncertainty into ELM-AE, we can treat the input weights as random variables following Gaussian distribution and propose weight uncertainty ELM-AE (WuELM-AE). In this paper, a neural network named multi layer ELM-RBF for multi-label learning (ML-ELM-RBF) is proposed. It is derived from radial basis function for multi-label learning (ML-RBF) and WuELM-AE. ML-ELM-RBF firstly stacks WuELM-AE to create a deep network, and then it conducts clustering analysis on samples features of each possible class to compose the last hidden layer. ML-ELM-RBF has achieved satisfactory results on single-label and multi-label data sets. Experimental results show that WuELM-AE and ML-ELM-RBF are effective learning algorithms. (C) 2016 Elsevier B.V. All rights reserved. |
| 资助项目 | National Natural Science Foundation of China[61379101] ; National Key Basic Research Program of China[2013CB329502] |
| WOS研究方向 | Computer Science |
| 语种 | 英语 |
| WOS记录号 | WOS:000375042300043 |
| 出版者 | ELSEVIER SCIENCE BV |
| 源URL | [http://119.78.100.204/handle/2XEOYT63/8529]  |
| 专题 | 中国科学院计算技术研究所期刊论文_英文 |
| 通讯作者 | Ding, Shifei |
| 作者单位 | 1.China Univ Min & Technol, Sch Comp Sci & Technol, Xuzhou 221116, Peoples R China 2.Chinese Acad Sci, Inst Comp Technol, Key Lab Intelligent Informat Proc, Beijing 100190, Peoples R China |
| 推荐引用方式 GB/T 7714 | Zhang, Nan,Ding, Shifei,Zhang, Jian. Multi layer ELM-RBF for multi-label learning[J]. APPLIED SOFT COMPUTING,2016,43:535-545. |
| APA | Zhang, Nan,Ding, Shifei,&Zhang, Jian.(2016).Multi layer ELM-RBF for multi-label learning.APPLIED SOFT COMPUTING,43,535-545. |
| MLA | Zhang, Nan,et al."Multi layer ELM-RBF for multi-label learning".APPLIED SOFT COMPUTING 43(2016):535-545. |
入库方式： OAI收割
来源：计算技术研究所
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