如何使用 mlr3tuningspaces 为 xgboost 超频带优化设置“预算”标签？答案

【问题标题】：How to set "budget" tag for xgboost hyperband optimization with mlr3tuningspaces?如何使用 mlr3tuningspaces 为 xgboost 超频带优化设置“预算”标签？
【发布时间】：2022-06-28 19:15:41
【问题描述】：

我正在尝试调整xgboost和超频带我想使用建议的默认调整空间mlr3tuningspaces包裹。但是，在使用 lts 时，我找不到如何用“预算”标记超参数。

下面，我转载了mlr3 超频带包示例来说明我的问题：

library(mlr3verse)
library(mlr3hyperband)
library(mlr3tuningspaces)

## this does not work, because I don\'t know how to tag a hyperparameter 
## with \"budget\" while using the suggested tuning space
search_space = lts(\"classif.xgboost.default\")
search_space$values

## this works because it has a hyperparameter (nrounds) tagged with \"bugdget\"
search_space = ps(
  nrounds = p_int(lower = 1, upper = 16, tags = \"budget\"), 
  eta = p_dbl(lower = 0, upper = 1),
  booster = p_fct(levels = c(\"gbtree\", \"gblinear\", \"dart\"))
)

# hyperparameter tuning on the pima indians diabetes data set
instance = tune(
  method = \"hyperband\",
  task = tsk(\"pima\"),
  learner = lrn(\"classif.xgboost\", eval_metric = \"logloss\"),
  resampling = rsmp(\"cv\", folds = 3),
  measures = msr(\"classif.ce\"),
  search_space = search_space,
  term_evals = 100
)

# best performing hyperparameter configuration
instance$result

标签： xgboost mlr3

【解决方案1】：

感谢您指出了这一点。我将预算标签添加到默认搜索空间。在此之前，您可以使用此代码。

library(mlr3hyperband)
library(mlr3tuningspaces)
library(mlr3learners)

# get learner with search space in one go
learner = lts(lrn("classif.xgboost"))

# overwrite nrounds with budget tag
learner$param_set$values$nrounds = to_tune(p_int(1000, 5000, tags = "budget"))

instance = tune(
  method = "hyperband",
  task = tsk("pima"),
  learner = learner,
  resampling = rsmp("cv", folds = 3),
  measures = msr("classif.ce"),
  term_evals = 100
)

2022 年 6 月 28 日更新

0.3.0 版中的新 API 是

learner = lts(lrn("classif.xgboost"), nrounds = to_tune(p_int(1000, 5000, tags = "budget"))

【讨论】：

感谢您提出的解决方法。当我运行learner = lts(lrn("classif.xgboost")) 行时，它会在 RStudio 中打开一个调试窗口，当我单击“继续”时它会工作，但我想我会提到它。
此错误已在 0.3.0 中修复