Move model_summary computations in Stacked Ensemble to Java

[exalate-issue-sync]

The model_summary calculation in Stacked Ensemble is created by doing a h2o.get_model() on each of the base models to get the algo type, on the client side, which is inefficient. The model summary data should be stored on the backend in a table or string or JSON object (whatever makes sense), and then when you do a h2o.get_model() on the SE, the model_summary should be populated on the client side by via REST (and some client/side post-processing), and then stored in the R and Python SE object.

Relationship to AutoML: Doing a h2o.get_model() on the SE (let's say... after you train the SE in AutoML), will bring SE object into R/Py memory for the first time, which generates the model summary and (currently) requires a get_model on all the base models.

This should also fix the missing model summary in python.

[exalate-issue-sync]

Erin LeDell commented: Let’s remove the R version from the client and surface in the normal way.

[exalate-issue-sync]

Erin LeDell commented: Can we also use the summary() output for print()?

[h2o-ops]

JIRA Issue Migration Info

Jira Issue: PUBDEV-7807
Assignee: Tomas Fryda
Reporter: Erin LeDell
State: Resolved
Fix Version: 3.40.0.1
Attachments: N/A
Development PRs: Available

Linked PRs from JIRA

#4984
#6443