Question

尝试在Rstudio中的http://learn.h2o.ai/content/tutorials/ensembles-stacking/index.html上找到H2OEnsemble上的示例时，遇到以下错误：

值[3L]出错：参数“training_frame”必须是有效的H2O H2OFrame或id

定义整体后

fit <- h2o.ensemble(x = x, y = y, 
                    training_frame = train, 
                     family = family, 
                     learner = learner, 
                     metalearner = metalearner,
                     cvControl = list(V = 5, shuffle = TRUE))

我安装了h2o和h2oEnsemble的最新版本，但问题仍然存在。我在这里`h2o.cbind` accepts only of H2OFrame objects - R已经看到h2o中的命名约定随着时间的推移而发生了变化，但我认为通过安装这两者的最新版本，这应该不再是问题。

有什么建议吗？

library(readr)
library(h2oEnsemble)  # Requires version >=0.0.4 of h2oEnsemble
library(cvAUC)  # Used to calculate test set AUC (requires version >=1.0.1 of cvAUC)
localH2O <-  h2o.init(nthreads = -1)  # Start an H2O cluster with nthreads = num cores on your machine





# Import a sample binary outcome train/test set into R
train <- h2o.importFile("http://www.stat.berkeley.edu/~ledell/data/higgs_10k.csv")
test <- h2o.importFile("http://www.stat.berkeley.edu/~ledell/data/higgs_test_5k.csv")
y <- "C1"
x <- setdiff(names(train), y)
family <- "binomial"

#For binary classification, response should be a factor
train[,y] <- as.factor(train[,y])  
test[,y] <- as.factor(test[,y])


# Specify the base learner library & the metalearner
learner <- c("h2o.glm.wrapper", "h2o.randomForest.wrapper", 
               "h2o.gbm.wrapper", "h2o.deeplearning.wrapper")
metalearner <- "h2o.deeplearning.wrapper"


# Train the ensemble using 5-fold CV to generate level-one data
# More CV folds will take longer to train, but should increase performance
fit <- h2o.ensemble(x = x, y = y, 
                    training_frame = train, 
                    family = family, 
                    learner = learner, 
                    metalearner = metalearner,
                    cvControl = list(V = 5, shuffle = TRUE))

Answer 1

最近通过批量查找/替换对h2o R代码进行的类名更改来引入此错误。这个改变也无意中应用于整体代码文件夹（我们目前有手动代替自动测试 - 很快就会自动防止这种事情）。我修复了这个bug。

要修复，请从GitHub重新安装h2oEnsemble包：

library(devtools)
install_github("h2oai/h2o-3/h2o-r/ensemble/h2oEnsemble-package")

感谢您的举报！为了更快地回复，请在此处发布错误和问题：https://groups.google.com/forum/#!forum/h2ostream

h2oensemble值[[3L]]（cond）中的错误：参数“training_frame”必须是有效的H2O H2OFrame或id

1 个答案: