Nothing
test_that("nnet + predict() works", {
skip_on_cran()
skip_if_not_installed("nnet")
skip_if_not_installed("parsnip")
suppressPackageStartupMessages(library(parsnip))
suppressPackageStartupMessages(library(nnet))
nnet_fit <- mlp("classification", hidden_units = 2) %>%
set_engine("nnet") %>%
fit(Species ~ ., data = iris)
x <- axe_call(nnet_fit)
expect_equal(x$fit$call, rlang::expr(dummy_call()))
x <- axe_env(nnet_fit)
expect_identical(attr(x$fit$terms, ".Environment"), rlang::base_env())
x <- axe_fitted(nnet_fit)
expect_equal(x$fit$fitted.values, numeric(0))
x <- butcher(nnet_fit)
expected_output <- predict(nnet_fit, iris[1:3, ])
expect_equal(predict(x, iris[1:3,]), expected_output)
})
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