Titlebook: Data Science and Classification; Vladimir Batagelj,Hans-Hermann Bock,Ale? ?iberna Conference proceedings 2006 Springer-Verlag Berlin Heide

寓言

書(shū)目名稱Data Science and Classification影響因子(影響力)




書(shū)目名稱Data Science and Classification影響因子(影響力)學(xué)科排名




書(shū)目名稱Data Science and Classification網(wǎng)絡(luò)公開(kāi)度




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書(shū)目名稱Data Science and Classification被引頻次




書(shū)目名稱Data Science and Classification被引頻次學(xué)科排名




書(shū)目名稱Data Science and Classification年度引用




書(shū)目名稱Data Science and Classification年度引用學(xué)科排名




書(shū)目名稱Data Science and Classification讀者反饋




書(shū)目名稱Data Science and Classification讀者反饋學(xué)科排名

Outshine

笨拙的你

Hierarchical Clustering for Boxplot Variables a new kind of symbolic variable. In addition, two different approaches to measure distances between boxplot variables are proposed. The usefulness of these distances is illustrated by means of a hierarchical clustering of boxplot data.

極端的正確性

deciduous

Metabolism of Proteins and Amino Acidsis generated to reproduce and show the limited conditions for the Fréchet distance. The proposed dissimilarity index is then compared with the Fréchet estimate and results illustrating its efficiency are reported.

CHOKE

Eric A. Heller MD,George D. Dangas MDbetween the units into account. The advantages of the new measure are illustrated by a study of the sensitivity against incomplete sampling and changes in the definition of the geographic units in two real data sets.

CHOKE

木訥

Arthur Freeman,Frank M. Dattilio a small categorical dataset. DIVCLUS-T is then compared empirically with two polythetic clustering methods: the Ward ascendant hierarchical clustering method and the k-means partitional method. The three algorithms are applied and compared on six databases of the UCI Machine Learning repository.

Conducive

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