On Mon, Sep 19, 2011 at 06:31:34PM +0100, Brian Holt wrote: > Does [Bayesian Inference](http://en.wikipedia.org/wiki/Bayesian_inference) > fall under the scope of scikit-learn? Probabilistic graphical models > are an exciting field in machine learning, with the theory going back > at least as far as 1982.
Probabilistic graphical models are not synonymous with Bayesian inference, despite the misleading "Bayesian networks" nomenclature. Graphical models are simply a formalism for expressing families of probability distributions on random variables and conditional independence assumptions between them. They can be (and usually are) fit by maximum likelihood or MAP estimation, meaning a single point estimate for the parameters. Bayesian inference involves placing priors on model parameters and (usually) integrating out model parameters, either analytically or with Markov Chain Monte Carlo estimates, to obtain a "predictive distribution" on test points. In general, it's difficult to write fully general graphical model code in such a way that learning and inference is acceptably fast, and usually specialized implementations of specific graphical models (i.e. Hidden Markov Models, Kalman filters, etc.) are significantly more efficient. It might be possible to include something like that in scikit-learn but it would be difficult to both write and maintain. As for the Bayesian inference setting, there is already PyMC, and I think the focus should be on improving that project rather than trying to make scikit-learn do everything. My $0.02, David ------------------------------------------------------------------------------ All the data continuously generated in your IT infrastructure contains a definitive record of customers, application performance, security threats, fraudulent activity and more. Splunk takes this data and makes sense of it. Business sense. IT sense. Common sense. http://p.sf.net/sfu/splunk-d2dcopy1 _______________________________________________ Scikit-learn-general mailing list [email protected] https://lists.sourceforge.net/lists/listinfo/scikit-learn-general
