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Back to basics to open the black box

Nature Machine Intelligence volume 6, pages 498–501 (2024)Cite this article

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Most research efforts in machine learning focus on performance and are detached from an explanation of the behaviour of the model. We call for going back to basics of machine learning methods, with more focus on the development of a basic understanding grounded in statistical theory.

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Fig. 1: Classical and modern algorithm-oriented machine learning.
Fig. 2: Frameworks of machine learning research.

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Acknowledgements

D.M. was funded by grants 22/06211-2 and 23/00256-7, São Paulo Research Foundation (FAPESP). J.B. was funded by grants 14/50937-1 and 2020/06950-4, São Paulo Research Foundation (FAPESP).

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Authors and Affiliations

  1. Department of Computer Science, Institute of Mathematics and Statistics, University of São Paulo, São Paulo, Brazil

    Diego Marcondes & Junior Barrera

  2. Department of Electrical and Computer Engineering, Texas A&M University, College Station, TX, USA

    Diego Marcondes

  3. Department of Statistics, Institute of Mathematics and Statistics, University of São Paulo, São Paulo, Brazil

    Adilson Simonis

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  1. Diego Marcondes
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  2. Adilson Simonis
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  3. Junior Barrera
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Correspondence to Diego Marcondes.

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Nature Machine Intelligence thanks Yiqun Chen for their contribution to the peer review of this work.

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Marcondes, D., Simonis, A. & Barrera, J. Back to basics to open the black box. Nat Mach Intell 6, 498–501 (2024). https://doi.org/10.1038/s42256-024-00842-6

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