Item type |
デフォルトアイテムタイプ_(フル)(1) |
公開日 |
2023-03-18 |
タイトル |
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タイトル |
Applying Cluster Ensemble to Adaptive Tree Structured Clustering |
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言語 |
en |
作成者 |
Yamaguchi, Takashi
Noguchi, Yuki
Ichimura, Takumi
Mackin, Kenneth J.
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アクセス権 |
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アクセス権 |
open access |
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アクセス権URI |
http://purl.org/coar/access_right/c_abf2 |
権利情報 |
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権利情報 |
(c) Copyright by IEEE SMC Hiroshima Chapter. |
主題 |
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主題Scheme |
NDC |
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主題 |
500 |
内容記述 |
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内容記述 |
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. In this paper, we apply cluster ensemble for each data partition of ATSC in order to improve stability. Cluster ensemble is a framework for improving partitioned clustering stability. As a result of applying cluster ensemble, ATSC yields unique clustering results that could not be yielded by previous hierarchical clustering methods. This is because a different class distances function is used in each division in ATSC. |
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言語 |
en |
出版者 |
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出版者 |
IEEE SMC Hiroshima Chapter |
言語 |
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言語 |
eng |
資源タイプ |
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資源タイプ識別子 |
http://purl.org/coar/resource_type/c_5794 |
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資源タイプ |
conference paper |
出版タイプ |
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出版タイプ |
VoR |
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出版タイプResource |
http://purl.org/coar/version/c_970fb48d4fbd8a85 |
関連情報 |
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識別子タイプ |
URI |
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関連識別子 |
http://www.hil.hiroshima-u.ac.jp/iwcia/2009/ |
収録物識別子 |
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収録物識別子タイプ |
ISSN |
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収録物識別子 |
1883-3977 |
開始ページ |
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開始ページ |
186 |
書誌情報 |
5th International Workshop on Computational Intelligence & Applications Proceedings : IWCIA 2009
5th International Workshop on Computational Intelligence & Applications Proceedings : IWCIA 2009
p. 186-191,
発行日 2009-11
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旧ID |
28421 |