This article will cover the basic theory behind logistic regression, the types of logistic regression, when to use them and take you through a worked example.

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.

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

Regression can be used on categorical responses to estimate probabilities and to classify.

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 ...

Bayesian analyses of multivariate binary or categorical outcomes typically rely on probit or mixed effects logistic regression models that do not have a marginal logistic structure for the individual ...

Through logistic regression analysis, it was found that pain severity, walking ability, self-care ability, physical function, ...

The results of this very basic analysis reveal that the number of times Aidan Chiles was sacked in a game and the support, or lack thereof, that he received from the Spartans’ run game were larger ...