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  2. Infer.NET - Wikipedia

    en.wikipedia.org/wiki/Infer.NET

    Infer.NET is a free and open source.NET software library for machine learning. [2] It supports running Bayesian inference in graphical models and can also be used for probabilistic programming . [ 3 ]

  3. Bayesian network - Wikipedia

    en.wikipedia.org/wiki/Bayesian_network

    A Bayesian network (also known as a Bayes network, Bayes net, belief network, or decision network) is a probabilistic graphical model that represents a set of variables and their conditional dependencies via a directed acyclic graph (DAG). [1] While it is one of several forms of causal notation, causal networks are special cases of Bayesian ...

  4. WinBUGS - Wikipedia

    en.wikipedia.org/wiki/WinBugs

    Originally intended to solve problems encountered in medical statistics, it soon became widely used in other disciplines, such as ecology, sociology, and geology. [2] The last version of WinBUGS was version 1.4.3, released in August 2007. Development is now focused on OpenBUGS, an open-source version of the package. WinBUGS 1.4.3 remains ...

  5. List of statistical software - Wikipedia

    en.wikipedia.org/wiki/List_of_statistical_software

    DAP – free replacement for SAS; Environment for DeveLoping KDD-Applications Supported by Index-Structures (ELKI) a software framework for developing data mining algorithms in Java; Epi Info – statistical software for epidemiology developed by Centers for Disease Control and Prevention (CDC). Apache 2 licensed [1]

  6. Bayesian linear regression - Wikipedia

    en.wikipedia.org/wiki/Bayesian_linear_regression

    Bayesian linear regression is a type of conditional modeling in which the mean of one variable is described by a linear combination of other variables, with the goal of obtaining the posterior probability of the regression coefficients (as well as other parameters describing the distribution of the regressand) and ultimately allowing the out-of-sample prediction of the regressand (often ...

  7. Markov blanket - Wikipedia

    en.wikipedia.org/wiki/Markov_blanket

    In a Bayesian network, the Markov boundary of node A includes its parents, children and the other parents of all of its children. In statistics and machine learning , when one wants to infer a random variable with a set of variables, usually a subset is enough, and other variables are useless.

  8. TK Solver - Wikipedia

    en.wikipedia.org/wiki/TK_Solver

    TK Solver's core technologies are a declarative programming language, algebraic equation solver, [1] an iterative equation solver, and a structured, object-based interface, using a command structure. [ 1 ] [ 7 ] The interface comprises nine classes of objects that can be shared between and merged into other TK files:

  9. An Essay Towards Solving a Problem in the Doctrine of Chances

    en.wikipedia.org/wiki/An_Essay_towards_solving_a...

    The essay includes an example of a man trying to guess the ratio of "blanks" and "prizes" at a lottery. So far the man has watched the lottery draw ten blanks and one prize. Given these data, Bayes showed in detail how to compute the probability that the ratio of blanks to prizes is between 9:1 and 11:1 (the probability is low - about 7.7%).