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test_that("plotResiduals with prediction object", {
set.seed(getOption("mlr.debug.seed"))
learner = makeLearner("regr.rpart")
mod = train(learner, regr.task)
preds = predict(mod, regr.task)
plot = plotResiduals(preds)
vdiffr::expect_doppelganger("plotResiduals - regr", plot)
# histogram
p_hist = plotResiduals(preds, type = "hist")
vdiffr::expect_doppelganger("plotResiduals - hist", p_hist)
# classif
learner = makeLearner("classif.rpart")
mod = train(learner, multiclass.task)
preds = predict(mod, multiclass.task)
p_hist = plotResiduals(preds)
vdiffr::expect_doppelganger("plotResiduals - classif", p_hist)
})
test_that("plotResiduals with BenchmarkResult", {
lrns = list(makeLearner("classif.ksvm"), makeLearner("classif.rpart"))
tasks = list(multiclass.task, binaryclass.task)
bmr = benchmark(lrns, tasks, hout, measures = getDefaultMeasure(multiclass.task))
# scatterplot
p_scatter = plotResiduals(bmr, type = "scatterplot")
vdiffr::expect_doppelganger("plotResiduals - scatter - bmr", p_scatter)
# histogram - bmr
plotResiduals(bmr, type = "hist")
p_hist_bmr = plotResiduals(bmr, type = "hist")
vdiffr::expect_doppelganger("plotResiduals - hist - bmr", p_hist_bmr)
p_hist_bmr_pretty = plotResiduals(bmr, pretty.names = FALSE)
vdiffr::expect_doppelganger("plotResiduals - hist - bmr - pretty", p_hist_bmr_pretty)
# check error when learner short names are not unique
lrns = list(
rf = makeLearner("classif.randomForest", id = "rf1"),
rf2 = makeLearner("classif.randomForest", id = "rf2")
)
res = benchmark(lrns, tasks, hout)
expect_error(plotBMRSummary(res),
"names are not unique")
})
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