翻訳と辞書 Words near each other ・ Adjustable grip hitch ・ Adjustable Ranging Telescope ・ Adjustable shelving ・ Adjustable spanner ・ Adjustable Wrench (Torke) ・ Adjustable-focus eyeglasses ・ Adjustable-rate mortgage ・ Adjustable-speed drive ・ Adjusted basis ・ Adjusted Compensation Payment Act ・ Adjusted cost base ・ Adjusted current yield ・ Adjusted ERA+ ・ Adjusted gross income ・ Adjusted Gross Revenue Insurance ・ Adjusted mutual information ・ Adjusted Peak Performance ・ Adjusted present value ・ Adjusted winner procedure ・ Adjusted world price ・ Adjusters International ・ Adjustierung ・ Adjusting entries ・ Adjustment ・ Adjustment (law) ・ Adjustment (psychology) ・ Adjustment clause ・ Adjustment disorder ・ Adjustment handle ・ Adjustment of status Dictionary Lists mini英和辞書 mini和英辞書 Webster 1913 Latin-English FOLDOC Wikipedia English ウィキペディア

翻訳と辞書　辞書検索 [ 開発暫定版 ] スポンサード リンク Adjusted mutual information ： ウィキペディア英語版 Adjusted mutual information In probability theory and information theory, adjusted mutual information, a variation of mutual information may be used for comparing clusterings. It corrects the effect of agreement solely due to chance between clusterings, similar to the way the adjusted rand index corrects the Rand index. It is closely related to variation of information: when a similar adjustment is made to the VI index, it becomes equivalent to the AMI.〔 The adjusted measure however is no longer metrical. ==Mutual Information of two Partitions== Given a set ''S'' of ''N'' elements $S=\backslash$, consider two partitions of ''S'', namely $U=\backslash$ with ''R'' clusters, and $V=\backslash$ with ''C'' clusters. It is presumed here that the partitions are so-called ''hard clusters;'' the partitions are pairwise disjoint: :$U\_i\backslash cap\; U\_j\; =\; V\_i\backslash cap\; V\_j\; =\; \backslash varnothing$ for all $i\backslash ne\; j$, and complete: :$\backslash cup\_^RU\_i=\backslash cup\_^C\; V\_j=S$ The mutual information of cluster overlap between ''U'' and ''V'' can be summarized in the form of an ''R''x''C'' contingency table $M=()^\_$, where $n\_$ denotes the number of objects that are common to clusters $U\_i$ and $V\_j$. That is, :$n\_=\backslash left|U\_i\backslash cap\; V\_j\backslash right|$ Suppose an object is picked at random from ''S''; the probability that the object falls into cluster $U\_i$ is: :$P(i)=\backslash frac$ The entropy associated with the partitioning ''U'' is: :$H(U)=-\backslash sum\_^R\; P(i)\backslash log\; P(i)$ ''H(U)'' is non-negative and takes the value 0 only when there is no uncertainty determining an object's cluster membership, ''i.e.'', when there is only one cluster. Similarly, the entropy of the clustering ''V'' can be calculated as: :$H(V)=-\backslash sum\_^C\; P\text{'}(j)\backslash log\; P\text{'}(j)$ where $P\text{'}(j)=/$. The mutual information (MI) between two partitions: :$MI(U,V)=\backslash sum\_^R\; \backslash sum\_^C\; P(i,j)\backslash log\; \backslash frac$ where ''P(i,j)'' denotes the probability that a point belongs to both the cluster $U\_i$ in ''U'' and cluster $V\_j$ in ''V'': :$P(i,j)=\backslash frac$ MI is a non-negative quantity upper bounded by the entropies ''H''(''U'') and ''H''(''V''). It quantifies the information shared by the two clusterings and thus can be employed as a clustering similarity measure. 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「Adjusted mutual information」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.