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Breiman's "Two Cultures" Revisited and Reconciled

Author

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  • Subhadeep

    (DEEP)

  • Mukhopadhyay
  • Kaijun Wang

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.

Suggested Citation

  • Subhadeep & Mukhopadhyay & Kaijun Wang, 2020. "Breiman's "Two Cultures" Revisited and Reconciled," Papers 2005.13596, arXiv.org.
  • Handle: RePEc:arx:papers:2005.13596
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    File URL: http://arxiv.org/pdf/2005.13596
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    1. Susan Athey & Julie Tibshirani & Stefan Wager, 2016. "Generalized Random Forests," Papers 1610.01271, arXiv.org, revised Apr 2018.
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