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 ...

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 ...

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

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 ...

I predict you'll find this logistic regression example with R to be helpful for gleaning useful information from common binary classification problems.

If you are a researcher or student with experience in multiple linear regression and want to learn about logistic regression, Logistic Regression Using the SAS System: Theory and Application is for ...

We apply an alternative statistical method, logistic regression, to estimate the strength of selection on multiple phenotypic traits. First, we argue that the logistic regression model is more ...

A new study investigated how logistic regression model training affects performance, and which features are best to include when examining datasets from individuals suffering from COVID-19.