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

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 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.

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.

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

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 ...

The regression diagnostics introduced by Pregibon for the dichotomous logistic model are extended to multiple groups viewed as a multivariate generalized linear model. We develop diagnostics which ...

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 ...