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context("resample_b632")
test_that("b632", {
res = makeResampleDesc("Bootstrap", iters = 2, predict = "both")
m = setAggregation(mmce, b632)
r = resample(makeLearner("classif.rpart"), task = binaryclass.task,
resampling = res, measure = m)
m1 = r$measures.train
m2 = r$measures.test
p = as.data.frame(r$pred)
ls11 = p[p$set == "train" & p$iter == 1, c("truth", "response")]
ls12 = p[p$set == "test" & p$iter == 1, c("truth", "response")]
ls1 = 0.368 * mean(ls11[, 1] != ls11[, 2]) + 0.632 * mean(ls12[, 1] != ls12[, 2])
ls21 = p[p$set == "train" & p$iter == 2, c("truth", "response")]
ls22 = p[p$set == "test" & p$iter == 2, c("truth", "response")]
ls2 = 0.368 * mean(ls21[, 1] != ls21[, 2]) + 0.632 * mean(ls22[, 1] != ls22[, 2])
ag = r$aggr
expect_equal(mean(c(ls1, ls2)), ag[["mmce.b632"]])
})
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