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ungraindesable.blogspot.com | ||
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alexanderetz.com
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| | | | | [This post has been updated and turned into a paper to be published in AMPPS] Much of the discussion in psychology surrounding Bayesian inference focuses on priors. Should we embrace priors, or should we be skeptical? When are Bayesian methods sensitive to specification of the prior, and when do the data effectively overwhelm it? Should... | |
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conscienceandconsciousness.com
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| | | | | A startling discovery of recent decades is that the laws of physics are fine-tuned for the possibility of life. That is to say, for life to be possible, certain numbers in physics had to fall in a certain narrow range. Some scientists and philosophers try to explain this by postulating an enormous number of universes,... | |
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profmattstrassler.com
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| | | | | Matt Strassler [April 12, 2012] It is common that, when reading about the universe or about particle physics, one will come across a phrase that somehow refers to ``matter and energy'', as though they are opposites, or partners, or two sides of a coin, or the two classes out of which everything is made. This | |
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blog.stata.com
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| | | Motivation You have just trained a gradient boosting machine (GBM) and a random forest (RF) classifier on your data using Stata's new h2oml command suite. Your GBM model achieves 87% accuracy on the testing data, and your RF model, 85%. It looks as if GBM is the preferred classifier, right? Not so fast. Why accuracy [...] | ||
