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context("surv_CoxBoost")
test_that("surv_CoxBoost", {
requirePackagesOrSkip(c("!Matrix", "!CoxBoost"), default.method = "load")
parset.list = list(
list(),
list(stepno = 10)
)
old.predicts.list = list()
for (i in seq_along(parset.list)) {
parset = parset.list[[i]]
y = as.matrix(surv.train[, surv.target])
colnames(y) = c("time", "status")
x = dropNamed(surv.train, surv.target)
penalty = 9 * sum(y[, "status"])
info = getFixDataInfo(surv.train, factors.to.dummies = TRUE,
ordered.to.int = TRUE)
pars = c(list(time = unname(y[, "time"]), status = unname(y[, "status"]),
return.score = FALSE, penalty = penalty,
x = as.matrix(fixDataForLearner(x, info))), parset)
m = do.call(CoxBoost::CoxBoost, pars)
p = as.numeric(predict(m,
newdata = as.matrix(fixDataForLearner(dropNamed(surv.test, surv.target),
info)), type = "lp"))
old.predicts.list[[i]] = as.numeric(p)
}
testSimpleParsets("surv.CoxBoost", surv.df, surv.target, surv.train.inds,
old.predicts.list, parset.list)
})
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