![](/images/graphics-bg.png)
A Fast Clustering Algorithm for Data with a Few Labeled Instances
Joint Authors
Yang, Jinfeng
Xiao, Yong
Wang, Jiabing
Ma, Qianli
Shen, Yanhua
Source
Computational Intelligence and Neuroscience
Issue
Vol. 2015, Issue 2015 (31 Dec. 2015), pp.1-10, 10 p.
Publisher
Hindawi Publishing Corporation
Publication Date
2015-03-11
Country of Publication
Egypt
No. of Pages
10
Main Subjects
Abstract EN
The diameter of a cluster is the maximum intracluster distance between pairs of instances within the same cluster, and the split of a cluster is the minimum distance between instances within the cluster and instances outside the cluster.
Given a few labeled instances, this paper includes two aspects.
First, we present a simple and fast clustering algorithm with the following property: if the ratio of the minimum split to the maximum diameter (RSD) of the optimal solution is greater than one, the algorithm returns optimal solutions for three clustering criteria.
Second, we study the metric learning problem: learn a distance metric to make the RSD as large as possible.
Compared with existing metric learning algorithms, one of our metric learning algorithms is computationally efficient: it is a linear programming model rather than a semidefinite programming model used by most of existing algorithms.
We demonstrate empirically that the supervision and the learned metric can improve the clustering quality.
American Psychological Association (APA)
Yang, Jinfeng& Xiao, Yong& Wang, Jiabing& Ma, Qianli& Shen, Yanhua. 2015. A Fast Clustering Algorithm for Data with a Few Labeled Instances. Computational Intelligence and Neuroscience،Vol. 2015, no. 2015, pp.1-10.
https://search.emarefa.net/detail/BIM-1057672
Modern Language Association (MLA)
Yang, Jinfeng…[et al.]. A Fast Clustering Algorithm for Data with a Few Labeled Instances. Computational Intelligence and Neuroscience No. 2015 (2015), pp.1-10.
https://search.emarefa.net/detail/BIM-1057672
American Medical Association (AMA)
Yang, Jinfeng& Xiao, Yong& Wang, Jiabing& Ma, Qianli& Shen, Yanhua. A Fast Clustering Algorithm for Data with a Few Labeled Instances. Computational Intelligence and Neuroscience. 2015. Vol. 2015, no. 2015, pp.1-10.
https://search.emarefa.net/detail/BIM-1057672
Data Type
Journal Articles
Language
English
Notes
Includes bibliographical references
Record ID
BIM-1057672