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context("classif_gausspr")
test_that("classif_gausspr", {
requirePackages("kernlab", default.method = "load")
parset.list = list(
list(),
list(kernel = "splinedot"),
list(tol = 0.2)
)
old.predicts.list = list()
old.probs.list = list()
for (i in seq_along(parset.list)) {
parset = parset.list[[i]]
pars = list(multiclass.formula, data = multiclass.train)
pars = c(pars, parset)
set.seed(getOption("mlr.debug.seed"))
m = do.call(kernlab::gausspr, pars)
p = kernlab::predict(m, newdata = multiclass.test[, -5], type = "response")
p2 = kernlab::predict(m, newdata = multiclass.test[, -5], type = "probabilities")
old.predicts.list[[i]] = p
old.probs.list[[i]] = p2
}
testSimpleParsets("classif.gausspr", multiclass.df, multiclass.target,
multiclass.train.inds, old.predicts.list, parset.list)
testProbParsets("classif.gausspr", multiclass.df, multiclass.target,
multiclass.train.inds, old.probs.list, parset.list)
})
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