plotD3_residual {auditor} R Documentation

## Plot Residuals vs Observed, Fitted or Variable Values in D3 with r2d3 package.

### Description

Function plotD3_residual plots residual values vs fitted, observed or variable values in the model.

### Usage

plotD3_residual(
object,
...,
variable = "_y_",
points = TRUE,
smooth = FALSE,
std_residuals = FALSE,
nlabel = 0,
point_count = NULL,
single_plot = TRUE,
scale_plot = FALSE,
background = FALSE
)

plotD3Residual(
object,
...,
variable = NULL,
points = TRUE,
smooth = FALSE,
std_residuals = FALSE,
point_count = NULL,
single_plot = TRUE,
scale_plot = FALSE,
background = FALSE
)


### Arguments

 object An object of class 'auditor_model_residual' created with model_residual function. ... Other 'auditor_model_residual' objects to be plotted together. variable Name of variable to order residuals on a plot. If variable="_y_", the data is ordered by a vector of actual response (y parameter passed to the explain function). If variable = "_y_hat_" the data on the plot will be ordered by predicted response. If variable = NULL, unordered observations are presented. points Logical, indicates whenever observations should be added as points. By default it's TRUE. smooth Logical, indicates whenever smoothed lines should be added. By default it's FALSE. std_residuals Logical, indicates whenever standardized residuals should be used. By default it's FALSE. nlabel Number of observations with the biggest residuals to be labeled. point_count Number of points to be plotted per model. Points will be chosen randomly. By default plot all of them. single_plot Logical, indicates whenever single or facets should be plotted. By default it's TRUE. scale_plot Logical, indicates whenever the plot should scale with height. By default it's FALSE. background Logical, available only if single_plot = FALSE. Indicates whenever background plots should be plotted. By default it's FALSE.

### Value

a r2d3 object

plot_residual

### Examples

dragons <- DALEX::dragons[1:100, ]

# fit a model
model_lm <- lm(life_length ~ ., data = dragons)

# use DALEX package to wrap up a model into explainer
lm_audit <- audit(model_lm, data = dragons, y = dragons$life_length) # validate a model with auditor mr_lm <- model_residual(lm_audit) # plot results plotD3_residual(mr_lm) library(randomForest) model_rf <- randomForest(life_length~., data = dragons) rf_audit <- audit(model_rf, data = dragons, y = dragons$life_length)
mr_rf <- model_residual(rf_audit)
plotD3_residual(mr_lm, mr_rf)



[Package auditor version 1.3.3 Index]