context("classif_randomForestSRCSyn")
test_that("classif_randomForestSRCSyn", {
requirePackagesOrSkip("randomForestSRC", default.method = "load")
parset.list = list(
list(),
list(ntree = 10L),
list(ntree = 5L, mtry = 4L),
list(ntree = 5L, nodesize = 2L, nsplit = 5, splitrule = "random")
)
old.predicts.list = list()
old.probs.list = list()
## binary
for (i in 1L:length(parset.list)) {
parset = parset.list[[i]]
parset = c(parset, list(data = binaryclass.train, formula = binaryclass.formula, forest = TRUE, na.action = "na.impute",
verbose = FALSE))
set.seed(getOption("mlr.debug.seed"))
m = do.call(randomForestSRC::rfsrcSyn, parset)
# seed needed because with few trees sometimes probabilities 0.5 occur
set.seed(getOption("mlr.debug.seed"))
p = randomForestSRC::rfsrcSyn(object = m, newdata = binaryclass.test, na.action = "na.impute", verbose = FALSE, membership = FALSE)$rfSynPred
old.predicts.list[[i]] = p$class
old.probs.list[[i]] = p$predicted[,binaryclass.class.levs[1]]
}
testSimpleParsets("classif.randomForestSRCSyn", binaryclass.df, binaryclass.target, binaryclass.train.inds, old.predicts.list, parset.list)
testProbParsets ("classif.randomForestSRCSyn", binaryclass.df, binaryclass.target, binaryclass.train.inds, old.probs.list, parset.list)
## multiclass
old.predicts.list = list()
old.probs.list = list()
for (i in 1L:length(parset.list)) {
parset = parset.list[[i]]
parset = c(parset, list(data = multiclass.train, formula = multiclass.formula, forest = TRUE, na.action = "na.impute",
verbose = FALSE))
set.seed(getOption("mlr.debug.seed"))
m = do.call(randomForestSRC::rfsrcSyn, parset)
p = randomForestSRC::rfsrcSyn(object = m, newdata = multiclass.test, na.action = "na.impute", verbose = FALSE, membership = FALSE)$rfSynPred
old.predicts.list[[i]] = p$class
old.probs.list[[i]] = p$predicted
}
testSimpleParsets("classif.randomForestSRCSyn", multiclass.df, multiclass.target, multiclass.train.inds, old.predicts.list, parset.list)
testProbParsets ("classif.randomForestSRCSyn", multiclass.df, multiclass.target, multiclass.train.inds, old.probs.list, parset.list)
})
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