ingredients (version 2.3.0)

calculate_oscillations: Calculate Oscillations for Ceteris Paribus Explainer

Description

Oscillations are proxies for local feature importance at the instance level. Find more details in Ceteris Paribus Oscillations Chapter.

Usage

calculate_oscillations(x, sort = TRUE, ...)

Value

an object of the class ceteris_paribus_oscillations

Arguments

x

a ceteris paribus explainer produced with the ceteris_paribus() function

sort

a logical value. If TRUE then rows are sorted along the oscillations

...

other arguments

References

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

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

calculate_oscillations(cp_rf)

# \donttest{
library("ranger")

apartments_rf_model <- ranger(m2.price ~ construction.year + surface + floor +
                                    no.rooms + district, data = apartments)

explainer_rf <- explain(apartments_rf_model,
                        data = apartments_test[,-1],
                        y = apartments_test$m2.price,
                        label = "ranger forest",
                        verbose = FALSE)

apartment <- apartments_test[1,]

cp_rf <- ceteris_paribus(explainer_rf, apartment)

calculate_oscillations(cp_rf)
# }