plot_residual: Plot Residuals vs Observed, Fitted or Variable Values

In auditor: Model Audit - Verification, Validation, and Error Analysis

Plot Residuals vs Observed, Fitted or Variable Values

Description

A plot of residuals against fitted values, observed values or any variable.

Usage

plot_residual(
  object,
  ...,
  variable = "_y_",
  smooth = FALSE,
  std_residuals = FALSE,
  nlabel = 0
)

plotResidual(
  object,
  ...,
  variable = NULL,
  smooth = FALSE,
  std_residuals = FALSE,
  nlabel = 0
)

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.
smooth	Logical, indicates whenever smoothed lines should be added. By default it's FALSE.
std_residuals	Logical, indicates whenever standardized residuals should be used.
nlabel	Number of observations with the biggest absolute values of residuals to be labeled.

Examples

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

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

lm_audit <- audit(model_lm, data = dragons, y = dragons$life_length)

# validate a model with auditor
mr_lm <- model_residual(lm_audit)

# plot results
plot_residual(mr_lm)
plot(mr_lm, type = "residual")

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)
plot_residual(mr_lm, mr_rf)
plot(mr_rf, mr_rf, type = "residual")

auditor documentation built on Nov. 2, 2023, 6:13 p.m.