It can be useful to visualize the sigmoid function, the key characteristic of a logistic regression model (Figure 1). The purpose of the function is to transform a probability (as a real number) into ...

Sigmoid functions map any real value into probability values between 0 and 1. ... Log-Odds and the Logit Function. In logistic regression, the logit function assigns a number to a probability.

The equation for p is called the logistic sigmoid function. When computing logistic regression, a z value can be anything from minus infinity to plus infinity, but a p value will always be between 0 ...

A variable undergoing logistic growth initially grows exponentially. After some time, the rate of growth decreases and the function levels off, forming a sigmoid, or s-shaped curve. For example ...