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Bayesian training

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  • Bayesian spam filtering — (pronounced BAYS ee ən, IPA pronunciation: IPA| [ beɪz.i.ən] , after Rev. Thomas Bayes), a form of e mail filtering, is the process of using a naive Bayes classifier to identify spam e mail.The first known mail filtering program to use a Bayes… …   Wikipedia

  • Bayesian poisoning — is a technique used by spammers to attempt to degrade the effectiveness of spam filters that rely on bayesian spam filtering. Bayesian filtering relies on Bayesian probability to determine whether an incoming mail is spam or is not spam ( ham , i …   Wikipedia

  • Bayesian network — A Bayesian network, Bayes network, belief network or directed acyclic graphical model is a probabilistic graphical model that represents a set of random variables and their conditional dependencies via a directed acyclic graph (DAG). For example …   Wikipedia

  • Bayesian information criterion — In statistics, in order to describe a particular dataset, one can use non parametric methods or parametric methods. In parametric methods, there might be various candidate models with different number of parameters to represent a dataset. The… …   Wikipedia

  • Bayesian-Filter — Der bayessche Filter (auch als bayesischer Filter bezeichnet) ist ein statistischer Filter, der auf dem bayesschen Wahrscheinlichkeitsbegriff aufbaut. Sein Name leitet sich vom englischen Mathematiker Thomas Bayes (etwa 1702−1761) ab. Markow… …   Deutsch Wikipedia

  • Bayesian Filter — Der bayessche Filter (auch als bayesischer Filter bezeichnet) ist ein statistischer Filter, der auf dem bayesschen Wahrscheinlichkeitsbegriff aufbaut. Sein Name leitet sich vom englischen Mathematiker Thomas Bayes (etwa 1702−1761) ab. Markow… …   Deutsch Wikipedia

  • Naive Bayes classifier — A naive Bayes classifier is a simple probabilistic classifier based on applying Bayes theorem with strong (naive) independence assumptions. A more descriptive term for the underlying probability model would be independent feature model . In… …   Wikipedia

  • One-shot learning — is an object categorization problem of current research interest in computer vision. Whereas most machine learning based object categorization algorithms require training on hundreds or thousands of images and very large datasets, one shot… …   Wikipedia

  • Statistical classification — See also: Pattern recognition See also: Classification test In machine learning, statistical classification is the problem of identifying the sub population to which new observations belong, where the identity of the sub population is unknown, on …   Wikipedia

  • Cross-validation (statistics) — Cross validation, sometimes called rotation estimation,[1][2][3] is a technique for assessing how the results of a statistical analysis will generalize to an independent data set. It is mainly used in settings where the goal is prediction, and… …   Wikipedia

  • Info-gap decision theory — is a non probabilistic decision theory that seeks to optimize robustness to failure – or opportuneness for windfall – under severe uncertainty,[1][2] in particular applying sensitivity analysis of the stability radius type[3] to perturbations in… …   Wikipedia

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