如何使用tune_nested()的mlr3tuning？

Question

rm(list = ls())
library(mlr3verse)
task <- tsk("pima")
learner <- lrn("classif.rpart")
measure <- msr("classif.ce")
inner_resample <- rsmp("cv", folds = 5)
outer_resample <- rsmp("cv", folds = 5)
search_space <- ps(
  cp = p_dbl(lower = 0.001, upper = 0.1)
)
rr <- tune_nested(
  method = "grid_search",
  resolution = 5,
  task = task,
  learner = learner,
  inner_resampling = inner_resample,
  outer_resampling = outer_resample,
  search_space = search_space,
  term_evals = 5
)

我总是会犯这样的错误：

Error in terminator_selection(term_evals, term_time) : 
  Assertion on 'term_evals' failed: Must be of type 'single integerish value' (or 'NULL'), not 'ParamSet/R6'.

我不知道我的密码有什么问题。有人能给我一些建议吗？非常感谢。

Answer 1

你发现了一个窃听器。我们会解决这个问题的。但是，如果您设置了measure，它应该可以工作。

library(mlr3verse)
task <- tsk("pima")
learner <- lrn("classif.rpart")
measure <- msr("classif.ce")
inner_resample <- rsmp("cv", folds = 5)
outer_resample <- rsmp("cv", folds = 5)
search_space <- ps(
  cp = p_dbl(lower = 0.001, upper = 0.1)
)
rr <- tune_nested(
  method = "grid_search",
  resolution = 5,
  task = task,
  learner = learner,
  inner_resampling = inner_resample,
  outer_resampling = outer_resample,
  measure = measure,
  search_space = search_space,
  term_evals = 5
)