show_observations: Adds a Layer with Observations to a Profile Plot

In ingredients: Effects and Importances of Model Ingredients

Adds a Layer with Observations to a Profile Plot

Description

Function show_observations adds a layer to a plot created with plot.ceteris_paribus_explainer for selected observations. Various parameters help to decide what should be plotted, profiles, aggregated profiles, points or rugs.

Usage

show_observations(
  x,
  ...,
  size = 2,
  alpha = 1,
  color = "#371ea3",
  variable_type = "numerical",
  variables = NULL
)

Arguments

x	a ceteris paribus explainer produced with function ceteris_paribus()
...	other explainers that shall be plotted together
size	a numeric. Size of lines to be plotted
alpha	a numeric between 0 and 1. Opacity of lines
color	a character. Either name of a color or name of a variable that should be used for coloring
variable_type	a character. If numerical then only numerical variables will be plotted. If categorical then only categorical variables will be plotted.
variables	if not NULL then only variables will be presented

Value

a ggplot2 layer

References

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

Examples

library("DALEX")
library("ingredients")

library("ranger")

rf_model <- ranger(survived ~., data = titanic_imputed, probability = TRUE)

explainer_rf <- explain(rf_model,
                        data = titanic_imputed[,-8],
                        y = titanic_imputed[,8],
                        label = "ranger forest",
                        verbose = FALSE)

selected_passangers <- select_sample(titanic_imputed, n = 100)
cp_rf <- ceteris_paribus(explainer_rf, selected_passangers)
cp_rf

plot(cp_rf, variables = "age", color = "grey") +
show_observations(cp_rf, variables = "age", color = "black") +
  show_rugs(cp_rf, variables = "age", color = "red")

ingredients documentation built on Jan. 15, 2023, 5:09 p.m.