The classification boundary is shown by the black line. Logistic Regression attains an accuracy of 0.969 and a F1-score of 0.628.

Samples of diseased cases and nondiseased controls are drawn at random from the population at risk. After classification according to the exposure of interest, subsamples of cases and controls are ...

The regression diagnostics introduced by Pregibon for the dichotomous logistic model are extended to multiple groups viewed as a multivariate generalized linear model. We develop diagnostics which ...