context("test-pipeline.R -- Basic pipeline functionality")
library(origami)
library(SuperLearner)
library(data.table)
data(cpp_imputed)
covars <- c("apgar1", "apgar5", "parity", "gagebrth", "mage", "meducyrs",
"sexn")
outcome <- "haz"
task <- sl3_Task$new(cpp_imputed, covariates = covars, outcome = outcome)
glm_learner <- Lrnr_glm$new()
test_screen_pipe <- function(screen_name_SuperLearner) {
set.seed(123)
screen_learner <-
Lrnr_pkg_SuperLearner_screener$new(screen_name_SuperLearner)
screen_glm <- make_learner(Pipeline, screen_learner, glm_learner)
fit <- screen_glm$train(task)
expect_equal(
fit$fit_object$learner_fits[[1]]$fit_object$selected,
names(fit$fit_object$learner_fits$Lrnr_glm_TRUE$coefficients)[-1]
)
}
test_that("Pipeline pipes selected covariates from screening algorithms", {
screens <- c(
"screen.glmnet", "screen.corP", "screen.corRank", "screen.randomForest"
)
lapply(screens, test_screen_pipe)
})
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