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k近傍の最大距離に基づくノイズにロバストな自己組織化マップに基づくクラスタリング手法


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Title: k近傍の最大距離に基づくノイズにロバストな自己組織化マップに基づくクラスタリング手法
Other Titles: A clustering method based on a self-organaizing map with maximum distance of k neighbors
Authors: 今村, 弘樹 / 藤村, 誠 / 黒田, 英夫
Authors (alternative): Imamura, Hiroki / Fujimura, Makoto / Kuroda, Hideo
Issue Date: Oct-2008
Publisher: 映像情報メディア学会
Citation: 映像情報メディア学会誌, 62(10), pp.1618-1623; 2008
Abstract: Clustering methods, which are based on Self-Organaizing Map, can not precisely classify data when noise data is included. We describe a clustering method that can precisely classify data even when noise data are included.
Keywords: クラスタリング / 自己組織化マップ / ノイズ / ロバスト性
URI: http://hdl.handle.net/10069/20847
ISSN: 13426907
Relational Links: http://ci.nii.ac.jp/naid/110006937671/
Type: Journal Article
Text Version: publisher
Appears in Collections:Articles in academic journal

Citable URI : http://hdl.handle.net/10069/20847

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