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 ...

Dependent and Independent Variables Logistic regression models have one dependent variable and several independent categorical or continuous predictor variables. Unlike standard linear regression ...

A closely related method is Pearson’s correlation coefficient, which also uses a regression line through the data points on a scatter plot to summarize the strength of an association between two ...

The random forest model significantly outperformed all other models, including the logistic regression model that the entire paper focuses on, with an eventual AUC of 0.936 and an accuracy of 0.918.

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 ...