todo-files/test_tune_tuneOptim.R

In berndbischl/mlr: Machine Learning in R

test_that("tuneOptim", {
  res = makeResampleDesc("CV", iters = 2)
  ps1 = makeParamSet(
    makeNumericParam("C", trafo = function(x) 2^x),
    makeNumericParam("sigma", trafo = function(x) 2^x)
  )
  ps2 = makeParamSet(
    makeNumericParam("cp", lower = 0.001, upper = 1),
    makeIntegerParam("minsplit", lower = 1)
  )
  ps3 = makeParamSet(
    makeNumericParam("cp", lower = 0.001, upper = 1),
    makeDiscreteParam("minsplit", values = c(1, 2))
  )
  lrn1 = makeLearner("classif.ksvm")
  lrn2 = makeLearner("classif.rpart")
  # nelder mead with optim
  ctrl = makeTuneControlOptim(method = "Nelder-Mead",
    start = list(C = 0, sigma = 0), maxit = 10)
  tr = tuneParams(lrn1, binaryclass.task, res, par.set = ps1, control = ctrl)
  ctrl = makeTuneControlOptim(method = "Nelder-Mead",
    start = list(cp = 0.05, minsplit = 5), maxit = 10)
  expect_error(tuneParams(lrn2, binaryclass.task, res, par.set = ps2, control = ctrl))

  ctrl = makeTuneControlOptim(method = "SANN",
    start = list(C = 0, sigma = 0), maxit = 10)
  tr = tuneParams(lrn1, binaryclass.task, res, par.set = ps1, control = ctrl)
  ctrl = makeTuneControlOptim(method = "SANN",
    start = list(cp = 0.05, minsplit = 5), maxit = 10)
  expect_error(tuneParams(lrn2, binaryclass.task, res, par.set = ps2, control = ctrl))

  ctrl = makeTuneControlOptim(method = "L-BFGS-B",
    start = list(C = 0, sigma = 0), maxit = 10)
  tr = tuneParams(lrn1, binaryclass.task, res, par.set = ps1, control = ctrl)
  ctrl = makeTuneControlOptim(method = "L-BFGS-B",
    start = list(cp = 0.05, minsplit = 5), maxit = 10)
  tr = tuneParams(lrn2, binaryclass.task, res, par.set = ps2, control = ctrl)

  expect_error(tuneParams(lrn2, multiclass.task, res, par.set = ps3, control = ctrl))
})