h2o.explain gives an error when the AutoML object was trained with a fold_column

[exalate-issue-sync]

There’s an error if you used a {{fold_column}} arg for AutoML. This seems to be related to {{model@parameters$x}} storing extra columns (like {{fold_column}}).

{code:r}library(h2o)

h2o.init()

#Import the titanic dataset
f <- "https://s3.amazonaws.com/h2o-public-test-data/smalldata/gbm_test/titanic.csv"
titanic <- h2o.importFile(f)

Set response column as a factor

y <- "survived"
titanic[y] <- as.factor(titanic[y])
x <- c('home.dest', 'cabin', 'embarked')

Split the dataset into train and test & add fold column

splits <- h2o.splitFrame(titanic, seed = 1, ratios = c(0.8))
train <- splits[[1]]
test <- splits[[2]]
train$fold <- h2o.kfold_column(train, nfolds = 5, seed = 1)

aml <- h2o.automl(y = y, x = x,
training_frame = train,
fold_column = "fold",
max_models = 5,
seed = 1)

h2o.explain(aml, test){code}

Gives this error:

{code:r}Error in [.H2OFrame(newdata, , x) :
No column(s) 'fold' found in pclass,survived,name,sex,age,sibsp,parch,ticket,fare,cabin,embarked,boat,body,home.dest
In addition: Warning messages:
1: In doTryCatch(return(expr), name, parentenv, handler) :
Test/Validation dataset is missing column 'fold': substituting in a column of NaN
2: In doTryCatch(return(expr), name, parentenv, handler) :
Test/Validation dataset is missing column 'fold': substituting in a column of NaN{code}

[h2o-ops]

JIRA Issue Details

Jira Issue: PUBDEV-8016
Assignee: Tomas Fryda
Reporter: Erin LeDell
State: Resolved
Fix Version: 3.32.1.1
Attachments: N/A
Development PRs: N/A