Geometric mean - Wikipedia
Example of the geometric mean: (red) is the geometric mean of and ,[1][2] is an example in which the line segment is given as a perpendicular to . is the diameter of a circle and . (Note: 10-second pause between each animation run). In mathematics, the geometric mean is a mean or average which indicates a central tendency of a finite collection of positive real numbers by using the product of thei
Naive Bayes classifier - Wikipedia
Example of a naive Bayes classifier depicted as a Bayesian Network In statistics, naive Bayes classifiers are a family of linear "probabilistic classifiers" which assumes that the features are conditionally independent, given the target class. The strength (naivety) of this assumption is what gives the classifier its name. These classifiers are among the simplest Bayesian network models.[1] Naive
Bayesian inference - Wikipedia
Toggle Inference over exclusive and exhaustive possibilities subsection
Bayesian probability - Wikipedia
Bayesian probability (/ˈbeɪziən/ BAY-zee-ən or /ˈbeɪʒən/ BAY-zhən)[1] is an interpretation of the concept of probability, in which, instead of frequency or propensity of some phenomenon, probability is interpreted as reasonable expectation[2] representing a state of knowledge[3] or as quantification of a personal belief.[4] The Bayesian interpretation of probability can be seen as an extension of
Bayesian average - Wikipedia
A Bayesian average is a method of estimating the mean of a population using outside information, especially a pre-existing belief,[1] which is factored into the calculation. This is a central feature of Bayesian interpretation. This is useful when the available data set is small.[2] Calculating the Bayesian average uses the prior mean m and a constant C. C is chosen based on the typical data set s
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