Breiman's "Two Cultures" Revisited and Reconciled
Not on the map. Why?
Abstract (arXiv)
In a landmark paper published in 2001, Leo Breiman described the tense standoff between two cultures of data modeling: parametric statistical and algorithmic machine learning. The cultural division between these two statistical learning frameworks has been growing at a steady pace in recent years. What is the way forward? It has become blatantly obvious that this widening gap between "the two cultures" cannot be averted unless we find a way to blend them into a coherent whole. This article presents a solution by establishing a link between the two cultures. Through examples, we describe the challenges and potential gains of this new integrated statistical thinking.
Key facts. Cited by 1 paper in the map (data through 14 Oct 2026). First posted on arXiv 27 May 2020.
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- 2021InfoGram and Admissible Machine Learningcited by 0
- 2021InfoGram and Admissible Machine Learning17 Aug 2021