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test_that("tuneGenSA", {
res = makeResampleDesc("CV", iters = 2)
ps1 = makeParamSet(
makeNumericParam("cp", lower = 0.001, upper = 1),
makeIntegerParam("minsplit", lower = 1, upper = 10)
)
ctrl1 = makeTuneControlGenSA(start = list(cp = 0.05, minsplit = 5L),
maxit = 5)
tr1 = tuneParams(makeLearner("classif.rpart"), multiclass.task, res,
par.set = ps1, control = ctrl1, measures = acc)
expect_number(tr1$y, lower = 0.8, upper = 1)
ps2 = makeParamSet(
makeNumericVectorParam("cutoff", lower = 0.0001, upper = 1, len = 3,
trafo = function(x) x / (1.1 * sum(x))),
makeIntegerParam("ntree", lower = 100, upper = 500)
)
ctrl2 = makeTuneControlGenSA(start = list(cutoff = c(1 / 3, 1 / 3, 1 / 3),
ntree = 200L),
maxit = 5, max.call = 3)
tr2 = tuneParams(makeLearner("classif.randomForest"), multiclass.task, res,
par.set = ps2, control = ctrl2)
expect_equal(ncol(as.data.frame(tr2$opt.path)), 4 + 1 + 2 + 2)
expect_number(tr2$y, lower = 0, upper = 0.2)
expect_true(is.list(tr2$x))
expect_equal(length(tr2$x), 2)
ps3 = makeParamSet(
makeNumericParam("cp", lower = 0.001, upper = 1),
makeDiscreteParam("minsplit", values = c(1, 2))
)
expect_error(tuneParams(makeLearner("classif.rpart"), multiclass.task, res,
par.set = ps3, control = ctrl1))
})
test_that("tuneGenSA with budget", {
res = makeResampleDesc("CV", iters = 2)
ps1 = makeParamSet(
makeNumericParam("cp", lower = 0.001, upper = 1),
makeIntegerParam("minsplit", lower = 1, upper = 10)
)
expect_error((makeTuneControlGenSA(start = list(cp = 0.05, minsplit = 5L),
max.call = 5, budget = 8)))
ctrl1 = makeTuneControlGenSA(start = list(cp = 0.05, minsplit = 5L),
max.call = 30, budget = 30)
tr1 = tuneParams(makeLearner("classif.rpart"), multiclass.task, res,
par.set = ps1, control = ctrl1)
expect_identical(getOptPathLength(tr1$opt.path), ctrl1$budget)
expect_identical(getOptPathLength(tr1$opt.path), ctrl1$extra.args$max.call)
})
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