Nothing

```
context("PipeOpKernelPCA")
test_that("PipeOpKernelPCA - basic properties", {
skip_if_not_installed("kernlab")
task = mlr_tasks$get("iris")
expect_datapreproc_pipeop_class(PipeOpKernelPCA, task = task,
deterministic_train = TRUE, deterministic_predict = TRUE, tolerance = 1e-4)
op = PipeOpKernelPCA$new()
expect_pipeop(op)
set.seed(1234)
result = op$train(list(task))
expect_task(result[[1]])
expect_equal(result[[1]]$data(), op$predict(list(task))[[1]]$data())
})
test_that("PipeOpKernelPCA - compare to kernlab::kpca", {
skip_if_not_installed("kernlab")
task = mlr_tasks$get("iris")
op = PipeOpKernelPCA$new()
expect_pipeop(op)
set.seed(1234)
result = op$train(list(task))
# Default parameters
dt = task$data()[, 2:5]
set.seed(1234)
pca = kernlab::kpca(as.matrix(dt))
expect_equal(dim(result[[1]]$data()[, -1]), dim(kernlab::rotated(pca)))
expect_equal(result[[1]]$data()[, -1], as.data.table(kernlab::rotated(pca)))
# Change some parameters
op2 = PipeOpKernelPCA$new(param_vals = list(kpar = list(sigma = 0.4), features = 4))
expect_pipeop(op2)
set.seed(1234)
result2 = op2$train(list(task))
set.seed(1234)
pca2 = kernlab::kpca(as.matrix(dt), kpar = list(sigma = 0.4), features = 4)
expect_true(all.equal(dim(kernlab::rotated(pca2)), dim(result2[[1]]$data()[, -1])))
dtres = as.matrix(result2[[1]]$data()[, -1])
dimnames(dtres) = NULL
expect_equal(dtres, kernlab::rotated(pca2))
})
```

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