# Exits
if (!requireNamespace("mlr", quietly = TRUE)) {
exit_file("Package mlr missing")
}
if (!requireNamespace("ranger", quietly = TRUE)) {
exit_file("Package ranger missing")
}
# Load required packages
suppressMessages({
library(mlr)
library(ranger)
})
# Generate Friedman benchmark data
friedman1 <- gen_friedman(seed = 101)
# Fit model(s)
set.seed(101)
task <- makeRegrTask("friedman", data = friedman1, target = "y")
lrnr <- makeLearner("regr.ranger", importance = "impurity")
fit <- mlr::train(lrnr, task = task)
# Compute model-based VI scores
vis <- vi_model(fit)
# Expect `vi()` and `vi_model()` to both work
expect_identical(
current = vi(fit, sort = FALSE),
target = vi_model(fit)
)
# Expectations for `vi_model()`
expect_identical(
current = vis$Importance,
target = unname(fit$learner.model$variable.importance)
)
# Expectations for `get_feature_names()`
expect_identical(
current = vip:::get_feature_names.WrappedModel(fit),
target = paste0("x", 1L:10L)
)
# Call `vip::vip()` directly
p <- vip(fit, method = "model", include_type = TRUE)
# Expect `p` to be a `"gg" "ggplot"` object
expect_identical(
current = class(p),
target = c("gg", "ggplot")
)
# Display VIPs side by side
grid.arrange(
vip(vis, include_type = TRUE),
p,
nrow = 1
)
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