Explain: Solve corner cases involving mapping between encoded varimps and predictor columns

[exalate-issue-sync]

Some explainability functions require variable importances for a predictor column not 1-hot encoded column.

Current implementation accomplishes that by first matching all the variable importances with predictor columns and from the remaining variable importances prefixes (from the parts separated by .) are created and the longest prefix present amongst the predictor columns is used as a valid column name.

For example:
{{df <- data.frame(cat = c("a.b","b.c","c.d"), cat.b=c("setosa", "versicolor", "virginica"))}}

varimps will be from some models with the following names:

• cat.a.b
• cat.b.c
• cat.c.d
• cat.b.setosa
• cat.b.versicolor
• cat.b.virginica

previous situation gets matched correctly but if we change the situation slightly:
{{df$b.c. <- df$cat.b}}

we cannot match it correctly by just using a prefix.

[exalate-issue-sync]

Michal Kurka commented: [~accountid:5e43370f5a495e0c91a74ebe] please update the fix version to the correct one, the old one was already released

[h2o-ops]

JIRA Issue Migration Info

Jira Issue: PUBDEV-7855
Assignee: Tomas Fryda
Reporter: Tomas Fryda
State: Resolved
Fix Version: 3.34.0.1
Attachments: N/A
Development PRs: Available

Linked PRs from JIRA

#5076