Understanding neural network activation functions is essential whether you use an existing software tool to perform neural network analysis of data or write custom neural network code. This article ...

Logistic regression is a powerful statistical method that is used to model the probability that a set of explanatory (independent or predictor) variables predict data in an outcome (dependent or ...

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, an ...

James McCaffrey explains what neural network activation functions are and why they're necessary, and explores three common activation functions. Understanding neural network activation functions is ...

In recent columns we showed how linear regression can be used to predict a continuous dependent variable given other independent variables 1,2. When the dependent variable is categorical, a common ...