Nothing
## Offset Terms
test_that("test model offsets", {
skip_if_not(TEST_ALL)
library(dials)
library(recipes)
df <- esoph
fo <- PoissonVariate(ncases) ~ agegp + alcgp + tobgp +
offset(log(ncases + ncontrols))
rec_df <- within(esoph, {
offset <- log(ncases + ncontrols)
ncases <- PoissonVariate(ncases)
})
rec <- recipe(ncases ~ agegp + alcgp + tobgp + offset, data = rec_df) %>%
role_pred(offset = offset, replace = TRUE)
test_fit <- function(model) {
has_offset <- switch(model@name,
"GBMModel" = {
function(x) !is.null(attr(x$Terms, "offset"))
},
"GLMModel" = function(x) !is.null(x$offset),
"GLMNetModel" = function(x) !is.null(x$offset))
model_fit <- expect_is(fit(fo, df, model = model), "MLModelFit")
expect_true(has_offset(model_fit))
expect_s4_class(predict(model_fit), "PoissonVariate")
model_fit <- expect_is(fit(rec, model = model), "MLModelFit")
expect_true(has_offset(model_fit))
expect_s4_class(predict(model_fit), "PoissonVariate")
}
## GBMModel fitting and prediction
test_fit(GBMModel())
## GLMModel fitting and prediction
test_fit(GLMModel())
## GLMMetModel fitting and prediction
test_fit(GLMNetModel())
})
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