print.aggregated_profiles_explainer: Prints Aggregated Profiles

In ingredients: Effects and Importances of Model Ingredients

Prints Aggregated Profiles

Description

Prints Aggregated Profiles

Usage

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

Arguments

x	an individual variable profile explainer produced with the aggregate_profiles() function
...	other arguments that will be passed to head()

Examples

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

model_titanic_glm <- glm(survived ~ gender + age + fare,
                         data = titanic_imputed, family = "binomial")

explain_titanic_glm <- explain(model_titanic_glm,
                               data = titanic_imputed[,-8],
                               y = titanic_imputed[,8])

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

head(cp_rf)

pdp_rf <- aggregate_profiles(cp_rf, variables = "age")
head(pdp_rf)


library("ranger")

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

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

cp_rf <- ceteris_paribus(explain_titanic_rf, selected_passangers)
cp_rf

pdp_rf <- aggregate_profiles(cp_rf, variables = "age")
head(pdp_rf)

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