问题描述
我正在学习R中用于机器学习的mlr3软件包。 我使用“保持”重采样将数据分为训练集和测试集，如何获得训练集的度量？似乎即使我将“ predict_set”指定为“ train”也只能给出测试集的度量。
> library(mlr3)
> task <- tsk("iris")
> learner <- lrn("classif.rpart")
> rs <- rsmp("holdout")
> rr <- resample(task,learner,rs)
INFO [12:28:49.941] Applying learner 'classif.rpart' on task 'iris' (iter 1/1)
> rr$aggregate(msr("classif.acc"))
classif.acc
0.96
> rr$score(msr("classif.acc"),predict_sets = "train")
task task_id learner learner_id resampling
1: <TaskClassif> iris <LearnerClassifRpart> classif.rpart <ResamplingHoldout>
resampling_id iteration classif.acc
1: holdout 1 0.96
> rr$score(msr("classif.acc"),predict_sets = "test")
task task_id learner learner_id resampling
1: <TaskClassif> iris <LearnerClassifRpart> classif.rpart <ResamplingHoldout>
resampling_id iteration prediction classif.acc
1: holdout 1 <PredictionClassif> 0.96
> sessionInfo()
R version 3.6.3 (2020-02-29)
Platform: x86_64-w64-mingw32/x64 (64-bit)
Running under: Windows 10 x64 (build 19041)
Matrix products: default
locale:
[1] LC_COLLATE=Chinese (Simplified)_China.936
[2] LC_CTYPE=Chinese (Simplified)_China.936
[3] LC_MONETARY=Chinese (Simplified)_China.936
[4] LC_NUMERIC=C
[5] LC_TIME=Chinese (Simplified)_China.936
attached base packages:
[1] stats graphics grDevices utils datasets methods base
other attached packages:
[1] mlr3_0.7.0
loaded via a namespace (and not attached):
[1] lgr_0.3.4 paradox_0.4.0 mlr3misc_0.5.0 codetools_0.2-16
[5] listenv_0.8.0 future_1.17.0 digest_0.6.25 crayon_1.3.4
[9] R6_2.4.1 mlr3measures_0.3.0 backports_1.1.6 future.apply_1.5.0
[13] uuid_0.1-4 data.table_1.12.8 rstudioapi_0.11 rpart_4.1-15
[17] checkmate_2.0.0 tools_3.6.3 parallel_3.6.3 compiler_3.6.3
[21] globals_0.12.5
解决方法
暂无找到可以解决该程序问题的有效方法，小编努力寻找整理中！
如果你已经找到好的解决方法，欢迎将解决方案带上本链接一起发送给小编。
小编邮箱:dio#foxmail.com (将#修改为@）