set.seed(1111)
# Random Forest analysis of model based recursive partitioning load data
data("BostonHousing", package = "mlbench")
BostonHousing <- BostonHousing[1:90, c("rad", "tax", "crim", "medv", "lstat")]
rfout <-
mobforest.analysis(
as.formula(medv ~ lstat), c("rad", "tax", "crim"),
mobforest_controls =
mobforest.control(ntree = 3, mtry = 2, replace = T, alpha = 0.05,
bonferroni = T, minsplit = 25), data = BostonHousing,
processors = 1, model = linearModel, seed = 1111)
# Run Tests
test_that("get.varimp was successful in all calculations.", {
# Crim Variable
expect_equal(unname(round(get.varimp(rfout)[1], 4)), 2.64)
# Tax Variable
expect_equal(unname(round(get.varimp(rfout)[3], 4)), -3.5508)
})
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