lapply(list.files(system.file("testthat", package = "mlr3"), pattern = "^helper.*\\.[rR]", full.names = TRUE), source)
generate_tasks.LearnerMultioutput = function(learner, N = 20L) { # nolint
set.seed(1)
# 2 classif 1 regr target
d = list(
"2d" = mlbench::mlbench.2dnormals(N, cl = 2, r = 2, sd = 0.1),
"wav" = mlbench::mlbench.waveform(N)
)
dt = cbind(map_dtc(d, "x"), map_dtc(d, "classes"))
set(dt, j = "t3", value = rnorm(N, sd = .1))
task = TaskMultioutput$new("sanity", dt, target = c("X2d", "wav", "t3"))
list(task)
}
registerS3method("generate_tasks", "LearnerMultioutput", generate_tasks.LearnerMultioutput,
envir = parent.frame()
)
sanity_check.PredictionMultioutput = function(prediction, task, ...) { # nolint
prediction$score(measures = msr("multioutput.default"), task = task) > 0
}
registerS3method("sanity_check", "PredictionMultioutput", sanity_check.PredictionMultioutput,
envir = parent.frame()
)
expect_prediction_multioutput = function(p) {
with(.GlobalEnv, expect_prediction)(p)
checkmate::expect_r6(p, "PredictionMultioutput",
public = c("row_ids", "truth", "predict_types")
)
}
Add the following code to your website.
For more information on customizing the embed code, read Embedding Snippets.