print.ceteris_paribus_explainer: Prints Individual Variable Explainer Summary

In ingredients: Effects and Importances of Model Ingredients

Prints Individual Variable Explainer Summary

Description

Prints Individual Variable Explainer Summary

Usage

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

Arguments

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

Examples

library("DALEX")
library("ingredients")
titanic_small <- select_sample(titanic_imputed, n = 500, seed = 1313)

# build a model
model_titanic_glm <- glm(survived ~ gender + age + fare,
                         data = titanic_small,
                         family = "binomial")

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

cp_glm <- ceteris_paribus(explain_titanic_glm, titanic_small[1,])
cp_glm


library("ranger")

apartments_rf_model <- ranger(m2.price ~., data = apartments)

explainer_rf <- explain(apartments_rf_model,
                        data = apartments_test[,-1],
                        y = apartments_test[,1],
                        label = "ranger forest",
                        verbose = FALSE)

apartments_small <- select_sample(apartments_test, 10)

cp_rf <- ceteris_paribus(explainer_rf, apartments_small)
cp_rf

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