View source: R/shap_aggregated.R
shap_aggregated | R Documentation |
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.
shap_aggregated(explainer, new_observations, order = NULL, B = 25, ...)
explainer |
a model to be explained, preprocessed by the |
new_observations |
a set of new observations with columns that correspond to variables used in the model. |
order |
if not |
B |
number of random paths |
... |
other parameters like |
an object of the shap_aggregated
class.
Explanatory Model Analysis. Explore, Explain and Examine Predictive Models. https://ema.drwhy.ai
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") bd_glm <- shap_aggregated(explain_titanic_glm, titanic_imputed[1:10, ]) bd_glm plot(bd_glm, max_features = 3)
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