loss_yardstick function

Wrapper for Loss Functions from the yardstick Package

The yardstick package provides many auxiliary functions for calculating the predictive performance of the model. However, they have an interface that is consistent with the tidyverse philosophy. The loss_yardstick function adapts loss functions from the yardstick package to functions understood by DALEX. Type compatibility for y-values and for predictions must be guaranteed by the user.

loss_yardstick(loss, reverse = FALSE, reference = 1)

Arguments

• loss: loss function from the yardstick package
• reverse: shall the metric be reversed? for loss metrics lower values are better. reverse = TRUE is useful for accuracy-like metrics
• reference: if the metric is reverse then it is calculated as reference - loss. The default value is 1.

Returns

loss function that can be used in the model_parts function

Examples

titanic_glm_model <- glm(survived~., data = titanic_imputed, family = "binomial")
 explainer_glm <- DALEX::explain(titanic_glm_model,
                                 data = titanic_imputed[,-8],
                                 y = factor(titanic_imputed$survived))
 # See the 'How to use DALEX with the yardstick package' vignette
 # which explains this model with measures implemented in the 'yardstick' package