plot.break_down_uncertainty function

Plot Generic for Break Down Uncertainty Objects

## S3 method for class 'break_down_uncertainty'
plot(
  x,
  ...,
  vcolors = DALEX::colors_breakdown_drwhy(),
  show_boxplots = TRUE,
  max_features = 10,
  max_vars = NULL
)

Arguments

• x: an explanation created with break_down_uncertainty
• ...: other parameters.
• vcolors: If NA (default), DrWhy colors are used.
• show_boxplots: logical if TRUE (default) boxplot will be plotted to show uncertanity of attributions
• max_features: maximal number of features to be included in the plot. By default it's 10.
• max_vars: alias for the max_features parameter.

Returns

a ggplot2 object.

Examples

library("DALEX")
library("iBreakDown")
set.seed(1313)
model_titanic_glm <- glm(survived ~ gender + age + fare,
                       data = titanic_imputed, family = "binomial")
explain_titanic_glm <- explain(model_titanic_glm,
                           data = titanic_imputed,
                           y = titanic_imputed$survived,
                           label = "glm")

sh_glm <- shap(explain_titanic_glm, titanic_imputed[1, ])

sh_glm
plot(sh_glm)

## Not run:

## Not run:
library("randomForest")
set.seed(1313)

model <- randomForest(status ~ . , data = HR)
new_observation <- HR_test[1,]

explainer_rf <- explain(model,
                        data = HR[1:1000,1:5])

bd_rf <- break_down_uncertainty(explainer_rf,
                           new_observation,
                           path = c(3,2,4,1,5),
                           show_boxplots = FALSE)
bd_rf
plot(bd_rf, max_features = 3)

# example for regression - apartment prices
# here we do not have intreactions
model <- randomForest(m2.price ~ . , data = apartments)
explainer_rf <- explain(model,
                        data = apartments_test[1:1000,2:6],
                        y = apartments_test$m2.price[1:1000])

bd_rf <- break_down_uncertainty(explainer_rf,
                                     apartments_test[1,],
                                     path = c("floor", "no.rooms", "district",
                                         "construction.year", "surface"))
bd_rf
plot(bd_rf)

bd_rf <- shap(explainer_rf,
              apartments_test[1,])
bd_rf
plot(bd_rf)
plot(bd_rf, show_boxplots = FALSE)
## End(Not run)

References

Explanatory Model Analysis. Explore, Explain and Examine Predictive Models. https://ema.drwhy.ai