plotD3_roc {auditor} R Documentation

## Receiver Operating Characteristic (ROC) in D3 with r2d3 package.

### Description

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.

### Usage

plotD3_roc(object, ..., nlabel = NULL, scale_plot = FALSE)


### Arguments

 object An object of class auditor_model_evaluation created with model_evaluation function. ... Other auditor_model_evaluation objects to be plotted together. nlabel Number of cutoff points to show on the plot. Default is NULL. scale_plot Logical, indicates whenever the plot should scale with height. By default it's FALSE.

### Value

a r2d3 object

plot_roc

### Examples

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)



[Package auditor version 1.3.3 Index]