Logistic regression can be thought of as an extension to, or a special case of, linear regression. If the outcome variable is a continuous variable, linear regression is more suitable.

Logistic regression is preferrable over a simpler statistical test such as chi-squared test or Fisher’s exact test as it can incorporate more than one explanatory variable and deals with possible ...

Linear and logistic regression models are essential tools for quantifying the relationship between outcomes and exposures. Understanding the mathematics behind these models and being able to apply ...

The simplest form of regression in Python is, well, simple linear regression. With simple linear regression, you're trying to ...

This article presents a complete demo program for logistic regression, using batch stochastic gradient descent training with weight decay. Compared to other binary classification techniques, logistic ...