plot.break_down_uncertainty {iBreakDown} | R Documentation |
Plot Generic for Break Down Uncertainty Objects
Description
Plot Generic for Break Down Uncertainty Objects
Usage
## 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 |
... |
other parameters. |
vcolors |
If |
show_boxplots |
logical if |
max_features |
maximal number of features to be included in the plot. By default it's |
max_vars |
alias for the |
Value
a ggplot2
object.
References
Explanatory Model Analysis. Explore, Explain and Examine Predictive Models. https://ema.drwhy.ai
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)
[Package iBreakDown version 2.1.2 Index]