DALEX (version 2.4.3)

shap_aggregated: SHAP aggregated values

Description

This function works in a similar way to shap function from iBreakDown but it calculates explanations for a set of observation and then aggregates them.

Usage

shap_aggregated(explainer, new_observations, order = NULL, B = 25, ...)

Value

an object of the shap_aggregated class.

Arguments

explainer

a model to be explained, preprocessed by the explain function

new_observations

a set of new observations with columns that correspond to variables used in the model.

order

if not NULL, then it will be a fixed order of variables. It can be a numeric vector or vector with names of variables.

B

number of random paths

...

other parameters like label, predict_function, data, x

References

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

Examples

library("DALEX")
set.seed(1313)
model_titanic_glm <- glm(survived ~ gender + age + fare,
                       data = titanic_imputed, family = "binomial")
explain_titanic_glm <- explain(model_titanic_glm,
                           data = titanic_imputed,
                           y = titanic_imputed$survived,
                           label = "glm")

# \donttest{
bd_glm <- shap_aggregated(explain_titanic_glm, titanic_imputed[1:10, ])
bd_glm
plot(bd_glm, max_features = 3)
# }