Logistic Regression is a widely used model in Machine Learning. It is used in binary classification, where output variable can only take binary values. Some real world examples where Logistic ...

Logistic regression is a powerful technique for fitting models to data with a binary response variable, but the models are difficult to interpret if collinearity, nonlinearity, or interactions are ...

A three-parameter family of survival models is introduced. The base-line density is derived and the main properties of the model, including a frailty interpretation, are discussed. Several different ...