# calculate_oscillations: Calculate Oscillations for Ceteris Paribus Explainer In ingredients: Effects and Importances of Model Ingredients

 calculate_oscillations R Documentation

## 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, ...)

### 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

### Value

an object of the class ceteris_paribus_oscillations

### 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)

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)

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