plotD3_roc {auditor} | R Documentation |
Receiver Operating Characteristic Curve is a plot of the true positive rate (TPR) against the false positive rate (FPR) for the different thresholds. It is useful for measuring and comparing the accuracy of the classificators.
plotD3_roc(object, ..., nlabel = NULL, scale_plot = FALSE)
object |
An object of class |
... |
Other |
nlabel |
Number of cutoff points to show on the plot. Default is |
scale_plot |
Logical, indicates whenever the plot should scale with height. By default it's |
a r2d3
object
data(titanic_imputed, package = "DALEX")
# fit a model
model_glm <- glm(survived ~ ., family = binomial, data = titanic_imputed)
# use DALEX package to wrap up a model into explainer
glm_audit <- audit(model_glm,
data = titanic_imputed,
y = titanic_imputed$survived)
# validate a model with auditor
eva_glm <- model_evaluation(glm_audit)
# plot results
plot_roc(eva_glm)
plot(eva_glm)
#add second model
model_glm_2 <- glm(survived ~ .-age, family = binomial, data = titanic_imputed)
glm_audit_2 <- audit(model_glm_2,
data = titanic_imputed,
y = titanic_imputed$survived,
label = "glm2")
eva_glm_2 <- model_evaluation(glm_audit_2)
plotD3_roc(eva_glm, eva_glm_2)