mlr3 多重测量 AutoFSelector

Question

我想询问如何修改我的代码，以便我可以获得多个性能度量作为输出。

我的代码如下：

ARMSS<-read.csv("Index ARMSS Proteomics Final.csv", row.names=1)

set.seed(123, "L'Ecuyer")

task = as_task_regr(ARMSS, target = "Index.ARMSS")

learner = lrn("regr.ranger", importance = "impurity")

set_threads(learner, n = 8)

resampling_inner = rsmp("cv", folds = 7)
measure = msrs(c("regr.rmse","regr.srho"))
terminator = trm("none")

at = AutoFSelector$new(
  learner = learner,
  resampling = resampling_inner,
  measure = measure,
  terminator = terminator,
  fselect = fs("rfe", n_features = 1, feature_fraction = 0.5, recursive = FALSE),
  store_models = TRUE)

然后我收到以下错误：

UseMethod("as_measure") 错误： 没有适用于“as_measure”的适用方法应用于“列表”类的对象

Answer 1

多目标优化的结果是Pareto front，即有多个最佳解决方案。 AutoFselector 需要一个解决方案来适应最终模型。因此，AutoFselector 仅适用于一种措施。