print.break_down_uncertainty function

Print Generic for Break Down Uncertainty Objects

Print Generic for Break Down Uncertainty Objects

## S3 method for class 'break_down_uncertainty' print(x, ...)

Arguments

  • x: an explanation created with break_down_uncertainty
  • ...: other parameters.

Returns

a data frame.

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$survived, label = "glm") bd_glm <- break_down_uncertainty(explain_titanic_glm, titanic_imputed[1, ]) bd_glm plot(bd_glm) ## Not run: ## Not run: library("randomForest") set.seed(1313) model <- randomForest(status ~ . , data = HR) new_observation <- HR_test[1,] explainer_rf <- explain(model, data = HR[1:1000,1:5], y = HR$status[1:1000], verbose = FALSE) bd_rf <- break_down_uncertainty(explainer_rf, new_observation) bd_rf # 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,]) bd_rf ## End(Not run)

References

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