Plot Autocorrelation Function of models' residuals.

plot_acf(object, ..., variable = NULL, alpha = 0.95)

plotACF(object, ..., variable = NULL, alpha = 0.95)

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.

alpha

Confidence level of the interval.

Value

A ggplot object.

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 exp_lm <- DALEX::explain(model_lm, data = dragons, y = dragons$life_length)
#> Preparation of a new explainer is initiated #> -> model label : lm (default) #> -> data : 100 rows 8 cols #> -> target variable : 100 values #> -> predict function : yhat.lm will be used (default) #> -> predicted values : numerical, min = 585.8311 , mean = 1347.787 , max = 2942.307 #> -> residual function : difference between y and yhat (default) #> -> residuals : numerical, min = -88.41755 , mean = -1.489291e-13 , max = 77.92805 #> A new explainer has been created!
# validate a model with auditor library(auditor) mr_lm <- model_residual(exp_lm) # plot results plot(mr_lm, type = "acf")
plot_acf(mr_lm)
library(randomForest) model_rf <- randomForest(life_length~., data = dragons) exp_rf <- DALEX::explain(model_rf, data = dragons, y = dragons$life_length)
#> Preparation of a new explainer is initiated #> -> model label : randomForest (default) #> -> data : 100 rows 8 cols #> -> target variable : 100 values #> -> predict function : yhat.randomForest will be used (default) #> -> predicted values : numerical, min = 756.6554 , mean = 1343.041 , max = 2457.22 #> -> residual function : difference between y and yhat (default) #> -> residuals : numerical, min = -187.2608 , mean = 4.745703 , max = 441.2011 #> A new explainer has been created!
mr_rf <- model_residual(exp_rf) plot_acf(mr_lm, mr_rf)
plot(mr_lm, mr_rf, type="acf")