Assembling ensembling: An adventure in approaches across disciplines

Amanda Bleichrodt, Lydia Bourouiba, Gerardo Chowell, Eric T. Lofgren, J. Michael Reed, Sadie J. Ryan, Nina H. Fefferman
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引用次数: 0

Abstract

When we think of model ensembling or ensemble modeling, there are many possibilities that come to mind in different disciplines. For example, one might think of a set of descriptions of a phenomenon in the world, perhaps a time series or a snapshot of multivariate space, and perhaps that set is comprised of data-independent descriptions, or perhaps it is quite intentionally fit *to* data, or even a suite of data sets with a common theme or intention. The very meaning of 'ensemble' - a collection together - conjures different ideas across and even within disciplines approaching phenomena. In this paper, we present a typology of the scope of these potential perspectives. It is not our goal to present a review of terms and concepts, nor is it to convince all disciplines to adopt a common suite of terms, which we view as futile. Rather, our goal is to disambiguate terms, concepts, and processes associated with 'ensembles' and 'ensembling' in order to facilitate communication, awareness, and possible adoption of tools across disciplines.
汇编汇编:跨学科方法探险
提到模型集合或集合建模,我们会想到不同学科中的多种可能性。例如,我们可能会想到对世界上某种现象的一组描述,也许是时间序列,也许是多元空间的快照,也许这组描述是由与数据无关的描述组成的,也许这组描述是有意与**数据相匹配的,甚至是具有共同主题或意图的一组数据集。集合"--集合在一起--的含义本身就能让人联想到不同学科甚至不同学科内部对现象的不同看法。在本文中,我们将对这些潜在视角的范围进行分类。我们的目标不是对术语和概念进行回顾,也不是说服所有学科采用一套共同的术语,我们认为这样做毫无用处。相反,我们的目标是明确与 "集合 "和 "集合 "相关的术语、概念和过程,以促进跨学科的交流、认识和可能的工具采用。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
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