Explore: Error Functions

In mathematics, the error function (also called the Gauss error function), often denoted by erf, is a function e r f : C → C {\displaystyle \mathrm {erf}

optimization and decision theory, a loss function or cost function (sometimes also called an error function) is a function that maps an event or values of one

function and activation functions do not matter as long as they and their derivatives can be evaluated efficiently. Traditional activation functions include

approximations can be found at: Error function#Approximation with elementary functions. In particular, small relative error on the whole domain for the cumulative

propagation of error) is the effect of variables' uncertainties (or errors, more specifically random errors) on the uncertainty of a function based on them

applications in computer science and telecommunications, error detection and correction (EDAC) or error control are techniques that enable reliable delivery

wide variety of sigmoid functions including the logistic and hyperbolic tangent functions have been used as the activation function of artificial neurons

complex error functions, provides a function voigt(x, sigma, gamma) with approximately 13–14 digits precision. It is based on the Faddeeva function as implemented

An off-by-one error or off-by-one bug (known by acronyms OBOE, OBOB, OBO and OB1) is a logic error that involves a number that differs from its intended

The Faddeeva function or Kramp function is a scaled complex complementary error function, w ( z ) := e − z 2 erfc ⁡ ( − i z ) = erfcx ⁡ ( − i z ) = e