Nothing
library(exprso)
suppressWarnings(RNGversion("3.5.0"))
o <- exprso(iris[,1:3], iris[,4])
set.seed(1)
arrays <- splitSample(o)
a <- buildANN(arrays[[1]])
b <- buildRF(arrays[[1]])
c <- buildSVM(arrays[[1]])
test_that("Continuous outcome models work", {
expect_error(
buildLDA(o)
)
expect_error(
buildNB(o)
)
expect_equal(
predict(a, arrays[[2]])@actual,
predict(b, arrays[[2]])@actual
)
expect_equal(
predict(b, arrays[[2]])@actual,
predict(c, arrays[[2]])@actual
)
})
# ss <- ctrlSplitSet(func = "splitSample", percent.include = 67)
# fs <- ctrlFeatureSelect(func = "fsNULL", top = 0)
# gs <- ctrlGridSearch(func = "plGrid", how = "buildSVM", top = c(2, 3, 0),
# kernel = c("linear", "radial"))
#
# test_that("Continuous outcome pl modules work", {
#
# set.seed(1)
# expect_equal(
# round(plCV(o, top = 0, how = "buildRF", fold = 2), 4),
# .9489
# )
#
# set.seed(1)
# expect_equal(
# round(plGrid(arrays[[1]], arrays[[2]], top = c(0, 2, 3), how = "buildRF",
# fold = 2)@summary$valid.acc, 4),
# c(.9645, .9244, .9643)
# )
#
# set.seed(1)
# boot <- plMonteCarlo(o, B = 3, ctrlSS = ss, ctrlFS = fs, ctrlGS = gs)
# expect_equal(
# round(calcMonteCarlo(boot), 4),
# .9619
# )
#
# set.seed(1)
# boot <- plNested(o, fold = 2, ctrlFS = fs, ctrlGS = gs, save = FALSE)
# expect_equal(
# round(calcNested(boot), 4),
# .9555
# )
#
# ens <- buildEnsemble(a, b, c)
# pred <- predict(ens, o)
# expect_equal(
# round(calcStats(pred)$acc, 4),
# .9286
# )
#
# ens <- buildEnsemble(boot)
# pred <- predict(ens, o)
# expect_equal(
# round(calcStats(pred)$acc, 4),
# .9536
# )
# })
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