- Bayesian Inference with Tears by Kevin
- Gibbs Sampling for the Uninitiated by Philip
my biased thoughts on the fields of natural language processing (NLP), computational linguistics (CL) and related topics (machine learning, math, funding, etc.)
06 November 2009
Getting Started In: Bayesian NLP
This isn't so much a post in the "GSI" series, but just two links that recently came out. Kevin Knight and Philip Resnik both just came out with tutorials for Bayesian NLP. They're both excellent, and almost entirely non-redundant. I highly recommend reading both. And I thank Kevin and Philip from the bottom of my heart, since I'd been toying with the idea of writing such a thing (for a few years!) and they've saved me the effort. I'd probably start with Kevin's and then move on to Philip's (which is more technically meaty), but either order is really fine.
I've been prepping my own tutorial. For practice, I wrote a series of blog entries, starting with What is Bayesian Statistical Inference?, walking through point estimates for a few posts [using baseball batting ability as a simple binomial example], then concluding with a full hierarchical beta-binomial.
ReplyDeleteOne of the hardest things I had to overcome in learning stats is sloppy random variable notation. I talk about this in a related post on what's wrong with probability notation.
Resnik and Hardisty need to keep event notation, Pr(X=x), separate from density notation, p(x). What's confusing to the novice audiences for whom they're writing is that for a discrete random variable X, Pr(X=x) = p(x). The problem is for continuous densities, where Pr(X=x) = 0, because you're integrating over a point rather than an interval of non-zero width (i.e. a measurable interval). When they write Pr(\pi) in equation (4) for the first MAP example, the value is zero, because p(\pi) is a continuous desnity. They really should write p(\pi) instead.
Thanks, Hal, for posting this, and thanks, Bob, for your very reasonable point regarding probability notation. I'm collecting this and other comments for the next version.
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