Identification of Statistically Significant Features from Random Forests
Jérôme Paul; Michel Verleysen; Pierre Dupont · 2013
WASTE classifies this as Replication Failure · AI classification, approximate
A previously reported effect did not replicate here — verify it holds before you build on it.
Abstract (excerpt)
Abstract. Embedded feature selection can be performed by analyzing the variables used in a Random Forest. Such a multivariate selection takes into account the interactions between variables but is not easy to interpret in a statistical…
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Metadata source: OpenAlex