Logistic regression employs a logistic function with a sigmoid (S-shaped) curve to map linear combinations of predictions and their probabilities. Sigmoid functions map any real value into ...

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 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 ...

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, ...

Logistic regression is a technique used to make predictions in situations where the item to predict can take one of just two possible values. For example, you might want to predict the credit ...

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.

Dimitris Bertsimas, Angela King, Logistic Regression: From Art to Science, Statistical Science, Vol. 32, No. 3 (August 2017), pp. 367-384 ...

Lukas Meier, Sara van de Geer, Peter Bühlmann, The Group Lasso for Logistic Regression, Journal of the Royal Statistical Society. Series B (Statistical Methodology), Vol. 70, No. 1 (2008), pp. 53-71 ...