Sometimes, iml:::inferTaskFromPrediction() function identifies tasks falsely as a regression task and then `pred$task = "regression" is falsely set.
Here is an example:
library(iml)
library(tidymodels)
data(german, package = "rchallenge")
credit = german[, c("duration", "amount", "purpose", "age",
"employment_duration", "housing", "number_credits", "credit_risk")]
# tidymodels
rf = rand_forest(mode = "classification", engine = "randomForest") %>%
fit(credit_risk ~ ., data = credit)
pred = Predictor$new(model = rf, data = credit, y = "credit_risk")
pred$task
#> [1] "unknown"
pred$task = NULL
pred$predict(credit[c(1, 2),])
pred$task
#> [1] "regression"
iml:::inferTaskFromPrediction(prediction = pred$predict(credit[c(1, 2),]))
#> [1] "regression"
(This issue was originally raised for the counterfactuals package, see dandls/counterfactuals#29)
Sometimes,
iml:::inferTaskFromPrediction()function identifies tasks falsely as aregressiontask and then `pred$task = "regression" is falsely set.Here is an example:
(This issue was originally raised for the counterfactuals package, see dandls/counterfactuals#29)