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how to compute a graphical gaussian model.
It's a good tutorial for machine learning and statistical modelling.
PMTK is a collection of Matlab/Octave functions. The toolkit is primarily designed to accompany Kevin Murphy's textbook, but can also be used independently of this book. The goal is to provide a unified conceptual and software framework encompassing machine learning, graphical models, and Bayesian statistics (hence the logo). (Some methods from frequentist statistics, such as cross validation, are also supported.) The toolbox is currently (December 2011) in maintenance mode, meaning that bugs will be fixed, but no new features will be added (at least not by Kevin or Matt).
PMTK supports a large variety of probabilistic models, including linear and logistic regression models (optionally with kernels), SVMs and gaussian processes, directed and undirected graphical models, various kinds
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