Assembling ensembling: An adventure in approaches across disciplines
CoRR(2024)
摘要
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.
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