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An adaptive fuzzy c-means clustering-based mixtures of experts model for unlabeled data classification
Xing, Hong-Jie1,2,3; Hua, Bao-Gang1,2
2008
发表期刊NEUROCOMPUTING
卷号71期号:4-6页码:1008-1021
文章类型Article
摘要Compared with labeled data, unlabeled data are more readily available. Currently, classification of unlabeled data is an open issue, especially for the case of unknown class number. In this paper, we propose an adaptive fuzzy c-means (FCM)-based mixtures of experts model to deal with the problem. In this model, each mixture of experts (ME) consists of two expert networks and a gating network. Two experts, namely. Gaussian neural network (GNN) and sigmoid neural network (SNN), are selected as two candidates. Two phases are employed to construct the proposed model. First, the whole input space is partitioned into several clusters using the FCM clustering algorithm. The number of clusters can be determined adaptively by a cluster validity function. Second, the proposed model is trained by a small fraction of samples which are closer to their corresponding cluster centers. A numerical study is made on several synthetic and real-world data sets. Compared with the other four models, the proposed model exhibits better generalization ability in dealing with problems of unsupervised classification. The experimental results also show that the extension version of the proposed model for semi-supervised classification is comparable to the (CVSVM)-V-3 approach. (c) 2007 Elsevier B.V. All rights reserved.
关键词Mixture Of Experts Gaussian Neural Network Unlabeled Data Classification
WOS标题词Science & Technology ; Technology
关键词[WOS]EM ALGORITHM ; TIME-SERIES ; VALIDITY ; NETWORKS
收录类别SCI
语种英语
WOS研究方向Computer Science
WOS类目Computer Science, Artificial Intelligence
WOS记录号WOS:000253663800057
引用统计
文献类型期刊论文
条目标识符http://ir.ia.ac.cn/handle/173211/9699
专题09年以前成果
作者单位1.Chinese Acad Sci, Inst Automat, Natl Lab Pattern Recognit, Beijing 100080, Peoples R China
2.Chinese Acad Sci, Beijing Grad Sch, Beijing, Peoples R China
3.Hebei Univ, Coll Math & Comp Sci, Baoding, Peoples R China
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Xing, Hong-Jie,Hua, Bao-Gang. An adaptive fuzzy c-means clustering-based mixtures of experts model for unlabeled data classification[J]. NEUROCOMPUTING,2008,71(4-6):1008-1021.
APA Xing, Hong-Jie,&Hua, Bao-Gang.(2008).An adaptive fuzzy c-means clustering-based mixtures of experts model for unlabeled data classification.NEUROCOMPUTING,71(4-6),1008-1021.
MLA Xing, Hong-Jie,et al."An adaptive fuzzy c-means clustering-based mixtures of experts model for unlabeled data classification".NEUROCOMPUTING 71.4-6(2008):1008-1021.
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