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)
loss function that can be used in the model_parts function
loss function from the yardstick package
shall the metric be reversed? for loss metrics lower values are better. reverse = TRUE
is useful for accuracy-like metrics
if the metric is reverse then it is calculated as reference - loss
. The default value is 1.
# \donttest{
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
# }
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