tests/testthat/test_cv_predictors.R

In mcboost: Multi-Calibration Boosting

skip_if_not_installed("mlr3")

test_that("TreeAuditorFitters work", {
  skip_on_cran()
  skip_if_not_installed("mlr3learners")
  skip_if_not_installed("rpart")
  rf = CVTreeAuditorFitter$new()
  out = rf$fit(iris[, 1:4], runif(150))
  expect_number(out[[1]])
  expect_is(out[[2]], "CVLearnerPredictor")
  expect_true(out[[2]]$is_fitted)
  out = out[[2]]$predict(iris[,1:4])
  expect_numeric(out)
})

test_that("MCBoost multicalibrate and predict_probs - CV Predictor", {
  skip_on_cran()
  skip_if_not_installed("mlr3learners")
  skip_if_not_installed("rpart")
  # Sonar task
  tsk = tsk("sonar")
  data = tsk$data(cols = tsk$feature_names)
  labels = tsk$data(cols = tsk$target_names)[[1]]
  set.seed(123L)
  mc = MCBoost$new(auditor_fitter = "CVTreeAuditorFitter")
  mc$multicalibrate(data, labels)

  expect_list(mc$iter_models, types = "CVLearnerPredictor")
  expect_list(mc$iter_partitions, types = "ProbRange")

  prds = mc$predict_probs(data)
  expect_numeric(prds, lower = 0, upper = 1, len = nrow(data))
})

test_that("Creating own CV Predictor works with different folds", {
  skip_on_cran()
  skip_if_not_installed("mlr3learners")
  skip_if_not_installed("rpart")
  # Sonar task
  tsk = tsk("sonar")
  data = tsk$data(cols = tsk$feature_names)
  labels = tsk$data(cols = tsk$target_names)[[1]]
  ln = lrn("regr.rpart")
  cvfit = CVLearnerAuditorFitter$new(ln, folds = 2L)
  set.seed(123L)
  mc = MCBoost$new(auditor_fitter = cvfit)
  mc$multicalibrate(data, labels)

  expect_equal(cvfit$learner$pipeop$param_set$values$resampling.folds, 2L)
  expect_list(mc$iter_models, types = "CVLearnerPredictor")
  expect_list(mc$iter_partitions, types = "ProbRange")

  prds = mc$predict_probs(data)
  expect_numeric(prds, lower = 0, upper = 1, len = nrow(data))
})