mlrパッケージr：機能選択順次順方向検索エラー：少なくとも1つの列を持つ

Question

Rでmlrパッケージを使用して、順方向前方検索を使用して、バッジ付きの学習者に機能選択を適用しようとしています。

d <- data.frame(a = rnorm(1000, mean = 1), 
        b = rnorm(1000, mean = 2), 
        c = rnorm(1000, mean = 3), 
        target = as.factor(rbinom(1000, 1, prob = 0.5))) 

t <- makeClassifTask(data = d, 
        target = 'target', 
        positive = '1') 

logreg.lrn <- makeLearner('classif.logreg') 
logreg_bagged.lrn <- makeBaggingWrapper(logreg.lrn) 

cntrl.sfs <- makeFeatSelControlSequential(method = "sfs", 
              alpha = 0.01, 
              max.features = 10, 
              maxit = 3) 

logreg_bagged_featsel.lrn <- makeFeatSelWrapper(logreg_bagged.lrn, 
               resampling = makeResampleDesc('CV', 
                       iters = 3), 
               measures = mmce, 
               control = cntrl.sfs) 

mlr::train(logreg_bagged_featsel.lrn, classif.task) 

は、次のエラーを返します：私は代わりに、順次後方検索を使用する場合

[FeatSel] Started selecting features for learner 'classif.logreg.bagged' 
With control class: FeatSelControlSequential 
Imputation value: 1 
[FeatSel-x] 1: 000 (0 bits) 
Error in mlr::train(logreg_bagged_featsel.lrn, classif.task) : 
    Assertion on '.newdata' failed: Must have at least 1 cols, but has 0 cols. 

、エラーは発生しません：

cntrl.sbs <- makeFeatSelControlSequential(method = "sbs", 
              alpha = 0.01, 
              max.features = 10, 
              maxit = 3) 

logreg_bagged_featsel.lrn <- makeFeatSelWrapper(logreg_bagged.lrn, 
               resampling = makeResampleDesc('CV', 
                       iters = 3), 
               measures = mmce, 
               control = cntrl.sbs) 

mlr::train(logreg_bagged_featsel.lrn, classif.task) 

[FeatSel] Started selecting features for learner 'classif.logreg.bagged' 
With control class: FeatSelControlSequential 
Imputation value: 1 
[FeatSel-x] 1: 111 (3 bits) 
[FeatSel-y] 1: mmce.test.mean=0.447; time: 0.0 min 
[FeatSel-x] 2: 011 (2 bits) 
[FeatSel-y] 2: mmce.test.mean=0.509; time: 0.0 min 
[FeatSel-x] 2: 101 (2 bits) 
[FeatSel-y] 2: mmce.test.mean=0.448; time: 0.0 min 
[FeatSel-x] 2: 110 (2 bits) 
[FeatSel-y] 2: mmce.test.mean=0.456; time: 0.0 min 
[FeatSel-x] 3: 001 (1 bits) 
[FeatSel-y] 3: mmce.test.mean=0.51; time: 0.0 min 
[FeatSel-x] 3: 100 (1 bits) 
[FeatSel-y] 3: mmce.test.mean=0.468; time: 0.0 min 
[FeatSel] Result: ac (2 bits) 
Model for learner.id=classif.logreg.bagged.featsel; learner.class=FeatSelWrapper 
Trained on: task.id = classif.df; obs = 1000; features = 3 
Hyperparameters: model=FALSE 

私はシーケンシャル前進のためにこの作業を行うことができますどのようにサーチ？ありがとう。

Answer 1

順次順方向検索は、空のモデル、つまりフィーチャなしで開始します。これは、袋詰めラッパーによってサポートされていません。このhereの問題を公開しました。