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“[.data.frame`”(num.response,x==y)中的r mlr surv.ranger错误:选择了未定义的列

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LeGeniusII · 技术社区 · 6 年前

准备数据(“卵巢”生存包):

require(pacman)
p_load(mlr, survival, tidyverse, ranger)
data("ovarian")
ovarian$rx <- factor(ovarian$rx, 
                     levels = c("1", "2"), 
                     labels = c("A", "B"))
ovarian$resid.ds <- factor(ovarian$resid.ds, 
                           levels = c("1", "2"), 
                           labels = c("no", "yes"))
ovarian$ecog.ps <- factor(ovarian$ecog.ps, 
                          levels = c("1", "2"), 
                          labels = c("good", "bad"))
ovarian <- ovarian %>% mutate(age_group = ifelse(age >=50, "old", "young"))
ovarian$age_group <- factor(ovarian$age_group)

现在,运行包“mlr”,surv.ranger:

trainTask <- makeSurvTask(data = ovarian, target = c("futime", "fustat"))
trainLearner <- makeLearner("surv.ranger", predict.type = "response")
train(trainLearner,trainTask)
Error in `[.data.frame`(num.response, x == y) : 
  undefined columns selected

为什么会出错?如何修复?

然后我尝试使用另一个示例数据集(mlr包中的lung.task),但得到了另一个错误:

trainLearner <- makeLearner("surv.ranger", predict.type = "response")
train(trainLearner,lung.task) # lung.task is from mlr package
Error in ranger::ranger(formula = NULL, dependent.variable.name = tn[1L],  : 
  argument ".weights" is missing, with no default

1 回复 | 直到 6 年前

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2

PhilippPro 6 年前

我花了很长时间才发现,但现在我发现了错误。它来自包Ranger中的参数respect.unordered.factors,这也不起作用:

ranger::ranger(formula = NULL, dependent.variable.name = "futime", status.variable.name = "fustat", data = ovarian, respect.unordered.factors = "order")

要解决此问题,可以将其设置为另一个值:

lrn <- makeLearner("surv.ranger", predict.type = "response", respect.unordered.factors = "partition")
lrn <- makeLearner("surv.ranger", predict.type = "response", respect.unordered.factors = "order")

编辑:在GitHub的最新Ranger版本中,此错误不再出现。要安装它,请使用以下命令并重新启动r:

devtools::install_github("imbs-hl/ranger")

这里也可以看到: https://github.com/imbs-hl/ranger/issues/359