Logistic model (source code)

= Logistic model
{wiki=Logistic_regression\#Logistic_model}

A logistic model maps a real-valued score $\eta$ to the probability $p=(1+e^{-\eta})^{-1}$, equivalently $\log(p/(1-p))=\eta$. <Logistic regression> takes $\eta$ to be an affine function of the predictors.