Logistic regression is a statistical method used to examine the relationship between a binary outcome variable and one or more explanatory variables. It is a special case of a regression model that ...

Logistic regression can handle categorical predictor variables, too. Similarly, the values to predict "red", "blue" were stored as strings. You can use numeric 0 and 1 if you wish. Logistic regression ...

We applied LR using the terms selected from the final MARS model to calculate odds ... (1984) On the existence of maximum likelihood estimates in logistic regression models. Biometrika 71:1–10.

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.

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 ...