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The premise of the abstract is flawed though. Who says statisticians aren't using algorithmic models? Perhaps the author doesn't but random forests, clustering,
by thousandautumns 8y ago
The premise of the abstract is flawed though. Who says statisticians aren't using algorithmic models? Perhaps the author doesn't but random forests, clustering, PCA, gaussian processes, and even neural networks are standard fare for many statisticians.
- cwyers 8y agoI mean, the author certainly used random forests, seeing as he invented them: https://www.berkeley.edu/news/media/releases/2005/07/07_breiman.shtml https://www.berkeley.edu/news/media/releases/2005/07/07_brei...
- thousandautumns 8y agoI can't help but notice he died in 2005. Perhaps the premise of the two cultures was more relevant a few decades ago, but in my more recent experience, its absolutely not the case.
- cwyers 8y agoThere is certainly cross-pollination between the two, and practitioners these days often adopt both. But the snide "machine learning is just statistics practiced by people who don't know what they're doing" comments you tend to see on HN ignore that machine learning was something that sprung up (largely in CS departments) to address challenges that statistics departments weren't addressing.