Add XGBoost and Naive Bayes to metalearner_algorithm options in Stacked Ensemble

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We should have all the available supervised algos as options for the metalearner algorithm. Currently its hardcoded to this list:

{quote}{{metalearner_algorithm = c("AUTO", "glm", "gbm", "drf", "deeplearning")}}{quote}

Should be:

{quote}{{metalearner_algorithm = c("AUTO", "glm", "gbm", "drf", "deeplearning", "xgboost", "naivebayes", "psvm",)}}{quote}

[exalate-issue-sync]

Erin LeDell commented: I removed “PSVM” from the title because we had to remove the algo from the list of metalearner options until a bug is fixed. [https://github.com//pull/4341|https://github.com//pull/4341|smart-link]

[exalate-issue-sync]

Abhinav Sharma commented: Hi team,

It seems that the {{naivebayes}} and {{xgboost}} meta-learners , the stacked ensemble does not accept the {{metalearner_params}} option at all with {{v3.30.0.4}}

{quote}Moreover, for the stacked ensemble with {{xgboost}} meta-learner it is not even possible to inspect the metalearner via {{se_model_with_xgb_metalearner.metalearner()}} as it throws an error.
{quote}

UPDATE: Whoops, for the second part I realized it’s because I was inspecting the model on a windows machine.

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Abhinav Sharma commented: Would you prefer that I create a bug report for this?

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Erin LeDell commented: [~accountid:557058:d55d2d14-5709-435a-be18-0436a70f4414] Thanks for the report. If you can, a new/separate Jira with an example would be great! (Otherwise we can create one).

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Abhinav Sharma commented: @erin, I’ve created and explained the task over here

[https://h2oai.atlassian.net/browse/PUBDEV-7907|https://h2oai.atlassian.net/browse/PUBDEV-7907|smart-link]

P.S. Thanks for the great work on Stacked Ensembles and H2O, I’ve learnt a lot from your thesis and subsequent work!

[h2o-ops]

JIRA Issue Migration Info

Jira Issue: PUBDEV-6965
Assignee: Sebastien Poirier
Reporter: Erin LeDell
State: Resolved
Fix Version: 3.28.0.4
Attachments: N/A
Development PRs: Available

Linked PRs from JIRA

#4273