博碩士論文 90522058 完整後設資料紀錄

DC 欄位 語言
DC.contributor資訊工程學系zh_TW
DC.creator李鴻聰zh_TW
DC.creatorHong-Chung Leeen_US
dc.date.accessioned2004-1-29T07:39:07Z
dc.date.available2004-1-29T07:39:07Z
dc.date.issued2004
dc.identifier.urihttp://ir.lib.ncu.edu.tw:444/thesis/view_etd.asp?URN=90522058
dc.contributor.department資訊工程學系zh_TW
DC.description國立中央大學zh_TW
DC.descriptionNational Central Universityen_US
dc.description.abstract群聚分析對於分析檢視資料之間的複雜結構是一種非常有效的工具,其應用領域相當廣泛,含蓋了生物資訊、影像處理和商業交易等範圍。群聚分析根據某些法則,比如最短距離或最小切割,來對資料作分群,使得同一群內的元素間關聯性強而群與群之間的關聯弱。 在此篇論文中,我們特別探討由G.W. Flake等人所提出的群聚演算法──最小切割樹演算法,並分析出此演算法對某些圖形無法作分群,亦即分群的結果就只有兩種可能:一群或 群,其中 為圖形的點數。我們得到一滿足此現像的充分必要條件,並且發現某些圖形滿足這個條件。zh_TW
dc.description.abstractClustering algorithms are effective tools for exploring the structure of complex data sets. There are a lot of applications for clustering algorithms, including bioinformatics, image recognition, business transactions, etc. The minimum cut tree clustering algorithm is using maximum flow techniques to cluster the data (graphs). We prove that two kinds of graph, i.e. graph with edge connectivity and a graph with a vertex connected to every other vertex, are the extreme conditions in the algorithm.en_US
DC.subject政治圖形zh_TW
DC.subject正規圖形zh_TW
DC.subject群聚演算法zh_TW
DC.subject最小切割樹zh_TW
DC.subject極端情形zh_TW
DC.subject邊連通zh_TW
DC.subjectextreme conditionsen_US
DC.subjectpolitician graphen_US
DC.subjectregular graphen_US
DC.subjectclusteringen_US
DC.subjectMinimum cut treeen_US
DC.subjectedge-connectivityen_US
DC.title最小切割樹群聚演算法極端情形之研究zh_TW
dc.language.isozh-TWzh-TW
DC.titleA Study on Extreme Conditions of Minimum Cut Tree Clustering Algorithmen_US
DC.type博碩士論文zh_TW
DC.typethesisen_US
DC.publisherNational Central Universityen_US

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