## 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 intreactionsmodel <- 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