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test_that("DummyFeaturesWrapper", {
methods = c("1-of-n", "reference")
for (m in methods) {
lrn = makeLearner("classif.ksvm")
lrn.w = makeDummyFeaturesWrapper(lrn, method = m)
bc.task.dummy = createDummyFeatures(bc.task, method = m)
# check if predict works
mod = train(lrn, bc.task.dummy, subset = 1:400)
mod.w = train(lrn.w, bc.task, subset = 1:400)
expect_equal(getLearnerModel(mod.w)$features, getTaskFeatureNames(bc.task.dummy))
expect_equal(getLearnerModel(mod.w)$features, attr(getLearnerModel(mod)@terms, "term.labels"))
# check if predict works
pred = predict(mod, bc.task.dummy, subset = 401:getTaskSize(bc.task))
pred.w = predict(mod.w, bc.task, subset = 401:getTaskSize(bc.task))
expect_equal(getPredictionResponse(pred), getPredictionResponse(pred.w))
}
})
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