Deep auto-encoder based clustering
文献类型:期刊论文
作者 | Song, Chunfeng1![]() ![]() ![]() ![]() |
刊名 | INTELLIGENT DATA ANALYSIS
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出版日期 | 2014 |
卷号 | 18页码:S65-S76 |
关键词 | Clustering deep auto-encoder non-linear transformation complicated data |
英文摘要 | For unsupervised problems like clustering, linear or non-linear data transformations are widely used techniques. Generally, they are beneficial to data representation. However, if data have a complicated structure, these techniques would be unsatisfying for clustering. In this paper, we propose a new clustering method based on the deep auto-encoder network, which can learn a highly non-linear mapping function. Via simultaneously considering data reconstruction and compactness, our method can obtain stable and effective clustering. Experimental results on four databases demonstrate that the proposed model can achieve promising performance in terms of normalized mutual information, cluster purity and accuracy. |
WOS标题词 | Science & Technology ; Technology |
类目[WOS] | Computer Science, Artificial Intelligence |
研究领域[WOS] | Computer Science |
关键词[WOS] | NEURAL-NETWORKS ; RECOGNITION |
收录类别 | SCI |
语种 | 英语 |
WOS记录号 | WOS:000347782000006 |
源URL | [http://ir.ia.ac.cn/handle/173211/3804] ![]() |
专题 | 自动化研究所_智能感知与计算研究中心 |
作者单位 | 1.North China Elect Power Univ, Sch Control & Comp, Beijing, Peoples R China 2.Chinese Acad Sci, Inst Automat, Beijing, Peoples R China 3.Southeast Univ, Sch Automat, Nanjing, Jiangsu, Peoples R China |
推荐引用方式 GB/T 7714 | Song, Chunfeng,Huang, Yongzhen,Liu, Feng,et al. Deep auto-encoder based clustering[J]. INTELLIGENT DATA ANALYSIS,2014,18:S65-S76. |
APA | Song, Chunfeng,Huang, Yongzhen,Liu, Feng,Wang, Zhenyu,&Wang, Liang.(2014).Deep auto-encoder based clustering.INTELLIGENT DATA ANALYSIS,18,S65-S76. |
MLA | Song, Chunfeng,et al."Deep auto-encoder based clustering".INTELLIGENT DATA ANALYSIS 18(2014):S65-S76. |
入库方式: OAI收割
来源:自动化研究所
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