# Load Friedman benchmark data
friedman1 <- readRDS("friedman.rds")$friedman1
friedman2 <- readRDS("friedman.rds")$friedman2
# Tests for package ranger (using ::)
if (require(ranger, quietly = TRUE) && require(parsnip, quietly = TRUE)) {
# Fit model(s)
fit1 <- ranger(y ~ ., friedman1) # NOTE: Data arg not named!
fit2 <- ranger(y ~ ., data = friedman1)
fit3 <- ranger(y ~ ., data = friedman2, probability = TRUE)
fit4 <- ranger(y ~ ., data = friedman2, probability = FALSE)
# Use parsnip interface
fit5 <- rand_forest(mtry = 3, trees = 2000, mode = "regression") %>%
set_engine("ranger", importance = 'impurity') %>%
fit(y ~ ., data = friedman1)
# Compute partial dependence for x.3
pd1 <- partial(fit1, pred.var = "x.3")
pd2 <- partial(fit2, pred.var = "x.3")
pd3 <- partial(fit3, pred.var = "x.3")
pd4 <- partial(fit3, pred.var = "x.3", prob = TRUE)
pd5 <- partial(fit5, pred.var = "x.3", train = friedman1)
ice1 <- partial(fit2, pred.var = "x.3", ice = TRUE)
ice2 <- partial(fit3, pred.var = "x.3", ice = TRUE)
ice3 <- partial(fit3, pred.var = "x.3", ice = TRUE, prob = TRUE)
# Expectations: partial()
expect_true(inherits(pd1, what = "partial"))
expect_true(inherits(pd2, what = "partial"))
expect_true(inherits(pd3, what = "partial"))
expect_true(inherits(pd4, what = "partial"))
expect_true(inherits(pd5, what = "partial"))
expect_true(inherits(ice1, what = "ice"))
expect_true(inherits(ice2, what = "ice"))
expect_true(inherits(ice3, what = "ice"))
expect_error(partial(fit4, pred.var = "x.3"))
}
Add the following code to your website.
For more information on customizing the embed code, read Embedding Snippets.