Breiman's "Two Cultures" Revisited and Reconciled

Subhadeep, Mukhopadhyay, Kaijun Wang

arXiv 27 May 2020 · Statistics — Machine Learning · 4 citations (OpenAlex)

arXiv:2005.13596 · PDF · DOI · OpenAlex · Extracted main text

Abstract

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.

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