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You may enjoy Leo Breiman's famous article "Statistical Modeling: The Two Cultures": http://projecteuclid.org/euclid.ss/1009213726 http://projecteuclid.org/eucl
by capnrefsmmat 10y ago
You may enjoy Leo Breiman's famous article "Statistical Modeling: The Two Cultures": http://projecteuclid.org/euclid.ss/1009213726 http://projecteuclid.org/euclid.ss/1009213726
What he calls "algorithmic modeling" is what I see as machine learning style thinking.
Naturally there's a lot of overlap and people in stats and ML often do related work (our statistics department, at CMU, collaborates a lot with the machine learning department), but there's a basic mindset difference.
- S4M 10y agoReally interesting article. After reading it, it seems that statistics are about devising a model (like y=ax+b+epsilon) and then fitting it on the data while machine learning algorithms are about letting the data make their own model).
- nfoz 10y agoI think a statistical view of that dichotomy is "parametric statistics" vs. "non-parametric statistics": https://en.wikipedia.org/wiki/Nonparametric_statistics https://en.wikipedia.org/wiki/Nonparametric_statistics I see "machine learning" as exploring computational approaches to non-parametric statistics. The idea of data-driven model-estimation is not outside the scope of "statistics".