Nothing
context("PipeOpNMF")
test_that("basic properties", {
skip_if_not_installed("NMF")
op = PipeOpNMF$new()
task = mlr_tasks$get("iris")
expect_pipeop(op)
expect_datapreproc_pipeop_class(PipeOpNMF, task = task, deterministic_train = FALSE)
})
test_that("feature selector", {
skip_if_not_installed("NMF")
op = PipeOpNMF$new()
dat = iris
dat$Sepal.Length[1L] <- -999
dat$test <- rep.int(c(TRUE, FALSE), times = 75L)
task = TaskClassif$new("test", backend = dat, target = "Species")
train_out = op$train(list(task))[[1L]]
expect_setequal(c("Sepal.Length", "test", paste0("NMF", 1:2)), train_out$feature_names)
})
test_that("parameters", {
skip_if_not_installed("NMF")
op = PipeOpNMF$new()
op$param_set$values$rank = 3L
op$param_set$values$nrun = 2L
op$param_set$values$seed = 999
task = mlr_tasks$get("iris")
train_out1 = op$train(list(task))[[1L]]
expect_subset(paste0("NMF", 1:3), train_out1$feature_names)
expect_equal(op$state@nrun, 2L)
expect_matrix(op$state@consensus)
train_out2 = op$train(list(task))[[1L]]
expect_equal(train_out1, train_out2)
})
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