Error when trying to use a fold column when number of folds < official number of levels in that column

[exalate-issue-sync]

I am trying to do to a pretty standard thing in ML and i am getting an error.

task:

• there’s a “cv” categorical column, which has 5 values (5-folds)
• i subset the frame by the cv column, to make train (1-4) and test (5)
• now i try to train a h2o.glm using train and i want to do 4-fold CV here using the 4 folds i have left, using the fold_column argument.
• however there’s an error in h2o.glm because its mad that train$cv says it has 5 levels, but only 4 are represented in the dataset. ive confimed this because it works if i use the original dataset with all 5 folds.
• i can’t find a way to re-level the frame to tell it that cv column only has 4 levels. h2o.setLevels() is just a re-naming tool but you cant change the cardinality of the domain.

C !Screen Shot 2021-02-21 at 5.03.46 PM.png|thumbnail! an we relax this restriction on fold_column in H2O algos?

[h2o-ops]

JIRA Issue Details

Jira Issue: PUBDEV-8024
Assignee: Michal Kurka
Reporter: Erin LeDell
State: Resolved
Fix Version: 3.32.1.1
Attachments: Available (Count: 1)
Development PRs: Available

[h2o-ops]

Attachments From Jira

Attachment Name: Screen Shot 2021-02-21 at 5.03.46 PM.png
Attached By: Erin LeDell
File Link:https://h2o-3-jira-github-migration.s3.amazonaws.com/PUBDEV-8024/Screen Shot 2021-02-21 at 5.03.46 PM.png

[h2o-ops]

Linked PRs from JIRA

#5345