tests/testthat/test_sboost.R

In jadonwagstaff/sboost: Machine Learning with AdaBoost on Decision Stumps

context("sboost Classifier")

num <- sboost(malware[-1], malware[1], 5, 1)
cat <- sboost(mushrooms[-1], mushrooms[1], 5, "p")

test_that("Arguments are properly used.", {
  expect_equal(num$outcomes[["positive"]], 1)
  expect_equal(cat$outcomes[["positive"]], "p")

  expect_equal(nrow(num$classifier), 5)
  expect_equal(nrow(cat$classifier), 5)

  expect_equal(round(num$training, digits = 5),
               data.frame(stumps = 5, features = 360, instances = 7597, positive_prevalence = 0.33882))
  expect_equal(round(cat$training, digits = 5),
               data.frame(stumps = 5, features = 22, instances = 8124, positive_prevalence = 0.48203))
})

test_that("Algorithm is classifying properly.", {
  expect_equal(num$classifier$feature, c("X195", "X356", "X148", "X290", "X250"))
  expect_equal(cat$classifier$feature, c("odor", "spore_print_color", "population", "odor", "population"))

  expect_equal(round(num$classifier$vote, digits = 5), c(0.52443, 0.37820, 0.38180, 0.25555, 0.23200))
  expect_equal(round(cat$classifier$vote, digits = 5), c(2.10010, 1.31712, 0.60860, 0.60788, 0.63077))

  expect_equal(num$classifier$left, c(1, 0, 1, 0, 1))
  expect_equal(cat$classifier$left, c("p", "p", "p", "p", "p"))

  expect_equal(num$classifier$right, c(0, 1, 0, 1, 0))
  expect_equal(cat$classifier$right, c("e", "e", "e", "e", "e"))

  expect_equal(num$classifier$split, c(0.5, 2.5, 79.5, 7.5, 0.5))
  expect_true(all(is.na(cat$classifier$split)))

  expect_true(all(is.na(num$classifier$left_categories)))
  expect_equal(cat$classifier$left_categories, c("c; f; m; p; s; y", "h; r; w", "s; v", "c; f; m; p; s; y", "c; v; y"))

  expect_true(all(is.na(num$classifier$right_categories)))
  expect_equal(cat$classifier$right_categories, c("a; l; n", "b; k; n; o; u; y", "a; c; n; y", "a; l; n", "a; n; s"))
})