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 ...

The CATMOD procedure can perform linear regression and logistic regression of response functions for data that can be represented in a contingency table. See Chapter 5, "Introduction to Categorical ...

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.

Logistic regression is a machine learning technique for binary classification. For example, you might want to predict the sex of a person (male or female) based on their age, state where they live, ...

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

Logistic regression enables you to investigate the relationship between a categorical outcome and a set of explanatory variables. The outcome, or response, can be dichotomous (yes, no) or ordinal (low ...

What are the advantages of logistic regression over decision trees? This question was originally answered on Quora by Claudia Perlich.