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翻訳と辞書　辞書検索 [ 開発暫定版 ] スポンサード リンク Davies–Bouldin index ： ウィキペディア英語版 Davies–Bouldin index The Davies–Bouldin index (DBI) (introduced by David L. Davies and Donald W. Bouldin in 1979) is a metric for evaluating clustering algorithms. This is an internal evaluation scheme, where the validation of how well the clustering has been done is made using quantities and features inherent to the dataset. This has a drawback that a good value reported by this method does not imply the best information retrieval. ==Preliminaries== Let ''C''''i'' be a cluster of vectors. Let ''X''''j'' be an n dimensional feature vector assigned to cluster ''C''''i''. : $S\_i\; =\; \backslash frac\; \backslash sum\_^$ Here $A\_i$ is the centroid of ''C''''i'' and ''T''''i'' is the size of the cluster ''i''. ''S''''i'' is a measure of scatter within the cluster. Usually the value of ''p'' is 2, which makes this a Euclidean distance function between the centroid of the cluster, and the individual feature vectors. Many other distance metrics can be used, in the case of manifolds and higher dimensional data, where the euclidean distance may not be the best measure for determining the clusters. It is important to note that this distance metric has to match with the metric used in the clustering scheme itself for meaningful results. : $M\_\; =\; \backslash left|\backslash left|A\_i-A\_j\backslash right|\backslash right|\_p\; =\; \backslash Bigl(\backslash displaystyle\backslash sum\_^\backslash left|a\_-a\_\backslash right|^p\backslash Bigr)^$ : $M\_$ is a measure of separation between cluster $C\_i$ and cluster $C\_j$. : $a\_$ is the ''k''th element of $A\_i$, and there are n such elements in ''A'' for it is an n dimensional centroid. Here ''k'' indexes the features of the data, and this is essentially the Euclidean distance between the centers of clusters ''i'' and ''j'' when ''p'' equals 2. 抄文引用元・出典: フリー百科事典『 ウィキペディア（Wikipedia）』 ■ウィキペディアで「Davies–Bouldin index」の詳細全文を読む スポンサード リンク 翻訳と辞書 : 翻訳のためのインターネットリソース Copyright(C) kotoba.ne.jp 1997-2016. All Rights Reserved.