Please use this identifier to cite or link to this item:
|Title:||Approximate distributed clustering by learning the confidence radius on Fisher discriminant ratio|
|Citation:||Shen, X.J., Zha, Z.J., Zhu, Q., Yang, H.B., Gu, P.Y. (2012). Approximate distributed clustering by learning the confidence radius on Fisher discriminant ratio. Electronics Letters 48 (14) : 839-841. ScholarBank@NUS Repository. https://doi.org/10.1049/el.2012.0347|
|Abstract:||Presented is a new clustering algorithm with approximate distributed clustering over a peer-to-peer (P2P) network. The Fisher discriminant ratio is used to dynamically learn the confidence radius based on the data distribution in every local peer. Experimental results show that the proposed approach can achieve better clustering accuracies than the DFEKM algorithm while preserving much lower bandwidth consumptions. © 2012 The Institution of Engineering and Technology.|
|Source Title:||Electronics Letters|
|Appears in Collections:||Staff Publications|
Show full item record
Files in This Item:
There are no files associated with this item.
checked on Mar 21, 2019
checked on Feb 9, 2019
Items in DSpace are protected by copyright, with all rights reserved, unless otherwise indicated.