Applying Cluster Ensemble to Adaptive Tree Structured Clustering
URI | http://harp.lib.hiroshima-u.ac.jp/hiroshima-cu/metadata/5175 | ||||||||||||||||||||||||
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File |
B1001.pdf
( 299.0 KB )
Open Date
:2010-01-08
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Title |
Applying Cluster Ensemble to Adaptive Tree Structured Clustering
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Abstract |
Adaptive tree structured clustering (ATSC) is our proposed divisive hierarchical clustering method that recursively divides a data set into 2 subsets using self-organizing feature map (SOM). In each partition, the data set is quantized by SOM and the quantized data is divided using agglomerative hierarchical clustering. ATSC can divide data sets regardless of data size in feasible time. On the other hand clustering result stability of ATSC is equally unstable as other divisive hierarchical clustering and partitioned clustering methods. |
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Description Peer Reviewed |
有
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Journal Title |
5th International Workshop on Computational Intelligence & Applications Proceedings : IWCIA 2009
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Spage |
186
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Epage |
191
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Published Date |
2009-11
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Publisher |
IEEE SMC Hiroshima Chapter
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ISSN |
1883-3977
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Language |
eng
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NIIType |
Conference Paper
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Text Version |
出版社版
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Rights |
©Copyright by IEEE SMC Hiroshima Chapter. Personal use of this material is permitted. However, permission to reprint/republish this material for advertising or promotional purposes or for creating new collective works for resale or redistribution to servers or lists, or to reuse any copyrighted component of this work in other works must be obtained from the IEEE
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hiroshima-cu
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