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v. t. e. In probability theory, the expected value (also called expectation, expectancy, expectation operator, mathematical expectation, mean, expectation value, or first moment) is a generalization of the weighted average. Informally, the expected value is the mean of the possible values a random variable can take, weighted by the probability ...
If a vector of predictions is generated from a sample of data points on all variables, and is the vector of observed values of the variable being predicted, with ^ being the predicted values (e.g. as from a least-squares fit), then the within-sample MSE of the predictor is computed as
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Propagation of uncertainty. In statistics, propagation of uncertainty (or propagation of error) is the effect of variables ' uncertainties (or errors, more specifically random errors) on the uncertainty of a function based on them. When the variables are the values of experimental measurements they have uncertainties due to measurement ...
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An interface in the Java programming language is an abstract type that is used to declare a behavior that classes must implement. They are similar to protocols. Interfaces are declared using the interface keyword, and may only contain method signature and constant declarations (variable declarations that are declared to be both static and final).
A sigmoid function refers specifically to a function whose graph follows the logistic function. It is defined by the formula: σ {\displaystyle \sigma (x)= {\frac {1} {1+e^ {-x}}}= {\frac {e^ {x}} {1+e^ {x}}}=1-\sigma (-x).} In many fields, especially in the context of artificial neural networks, the term "sigmoid function" is correctly ...
Expected mean squares. In statistics, expected mean squares (EMS) are the expected values of certain statistics arising in partitions of sums of squares in the analysis of variance (ANOVA). They can be used for ascertaining which statistic should appear in the denominator in an F-test for testing a null hypothesis that a particular effect is ...