model_roc: ROC curve: receiver operating characteristic curve

In Dfranzani/MTRGLM: Generalized linear model metrics

ROC curve: receiver operating characteristic curve

Description

model_roc() returns the ROC curve by calculating the true positive rate (TPR) and false positive rate (FPR), as well as the area under the curve. The graph allows you to evaluate the discrimination capacity of the model.

Usage

model_roc(y_train, y_train_prob, y_test, y_test_prob)

Arguments

y_train	Values of the response variable in training set.
y_train_prob	Probabilities of the response variable in training set.
y_test	Values of the response variable in test set.
y_test_prob	Probabilities of the response variable in test set.

Dfranzani/MTRGLM documentation built on March 28, 2024, 1:34 a.m.