灰聚類演算法

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Title:	灰聚類演算法
Other Titles:	The Grey Clustering Algorithm
Authors:	翁慶昌;賴宏仁
Contributors:	淡江大學電機工程學系
Keywords:	灰色關聯分析;集群分析;門檻值;集群演算法;Grey Relational Analysis;Clustering Analysis;Threshold Value;Clustering Algorithm
Date:	2000-11
Issue Date:	2014-02-13 11:15:17 (UTC+8)
Abstract:	本文提出一個以資料間的灰關聯分析為基礎的資料聚類方法。由資料間的灰關聯分析結果，我們可以經由一個閥值的設定來判斷資料與資料間的相似關係，再利用這個相似度的測量結果將資料分類。由於閥值的決定關係到資料聚類的結果，在本文中提出一個測量效能的方法來協助選擇適當的閥值。此一具有自動選擇參數的灰聚類演算法由於不需做任何人為的設定，即可以將資料自動聚類，為一非監督式的聚類方法。本文最後會利用幾個例子來說明灰聚類演算法的資料聚類結果。 A data clustering algorithm based on the grey relational analysis ofdata is proposed. From the result of the grey relational analysis, wecan determine the similarity between data by setting a properthreshold value, and the similarity measurement can apply to dataclustering. Since the determination of the threshold value willdirectly affect the result of the clustering, we address a performancemeasurement to select a suitable threshold value. The grey clusteringalgorithm need not a priori setting of parameter, and can clusteringthe data directly. Some examples of data clustering are utilized toillustrate the effective of this algorithm.
Relation:	2000年灰色系統理論與應用研討會論文集，頁277-284
Appears in Collections:	[Graduate Institute & Department of Electrical Engineering] Proceeding

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灰聚類演算法_中文摘要.docx	摘要	20Kb	Microsoft Word	306	View/Open
灰聚類演算法_英文摘要.docx	摘要	20Kb	Microsoft Word	109	View/Open

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