Logistic regression is a powerful statistical method that is used to model the probability that a set of explanatory (independent or predictor) variables predict data in an outcome (dependent or ...

Basic logistic regression can be used for binary classification, for example predicting if a person is male or female based on predictors such as age, height, annual income, and so on. Multi-class ...

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.

A machine learning model may help predict mortality for hospitalized patients with cirrhosis at the time of admission, ...

Robert D. Gibbons, Donald Hedeker, Random Effects Probit and Logistic Regression Models for Three-Level Data, Biometrics, Vol. 53, No. 4 (Dec., 1997), pp. 1527-1537 Link account to institutional ...

If the signal to noise ratio is low (it is a ‘hard’ problem) logistic regression is likely to perform best. In technical terms, if the AUC of the best model is below 0.8, logistic very clearly ...