如何从 `party::cforest()` 获取 OOB 混淆矩阵？

Question

randomForest 包中的randomForest() 函数非常有用provides the confusion matrix based on out-of-bag prediction in classification。

party 包does not seem to provide this information 中的cforest() 函数。在party documentation 中搜索“confusion”并没有产生任何有用的信息，searching here 也没有。也许我忽略了什么？

有没有办法获得 party::cforest() 分类模型的 OOB 混淆矩阵？

Answer 1

我从party.pdf

中取出了这个

比较，用OOB = TRUE和FALSE P>

set.seed(290875)
### honest (i.e., out-of-bag) cross-classification of
### true vs. predicted classes
data("mammoexp", package = "TH.data")
table(mammoexp$ME, predict(cforest(ME ~ ., data = mammoexp,
                                   control = cforest_unbiased(ntree = 50)),
                           OOB = TRUE))


                  Never Within a Year Over a Year
  Never           195            31           8
  Within a Year    57            46           1
  Over a Year      54            20           0

table(mammoexp$ME, predict(cforest(ME ~ ., data = mammoexp,
                                   control = cforest_unbiased(ntree = 50)),
                           OOB = FALSE))
  Never Within a Year Over a Year
  Never           212            22           0
  Within a Year    58            46           0
  Over a Year      54            17           3