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test_that("classif_plr", {
requirePackagesOrSkip("stepPlr", default.method = "load")
parset.list1 = list(
list(),
list(cp = 0.005),
list(cp = "aic"),
list(cp = "bic", lambda = 1e-2)
)
parset.list2 = list(
list(),
list(cp = 0.005),
list(cp.type = "aic"),
list(cp.type = "bic", lambda = 1e-2)
)
old.predicts.list = list()
old.probs.list = list()
for (i in seq_along(parset.list1)) {
parset = parset.list1[[i]]
x = binaryclass.train
y = as.numeric(x[, binaryclass.class.col] == binaryclass.class.levs[1L])
x[, binaryclass.class.col] = NULL
pars = list(x = x, y = y)
pars = c(pars, parset)
m = do.call(stepPlr::plr, pars)
newx = binaryclass.test
newx[, binaryclass.class.col] = NULL
p = stepPlr::predict.plr(m, newx = newx, type = "class")
p = ifelse(p == 1, binaryclass.class.levs[1L], binaryclass.class.levs[2L])
p2 = stepPlr::predict.plr(m, newx = newx, type = "response")
old.predicts.list[[i]] = p
old.probs.list[[i]] = p2
}
testSimpleParsets("classif.plr", binaryclass.df, binaryclass.target,
binaryclass.train.inds, old.predicts.list, parset.list2)
testProbParsets("classif.plr", binaryclass.df, binaryclass.target,
binaryclass.train.inds, old.probs.list, parset.list2)
})
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