Stacked Ensemble: enable using previously persisted base models

h2oai / h2o-3

H2O is an Open Source, Distributed, Fast & Scalable Machine Learning Platform: Deep Learning, Gradient Boosting (GBM) & XGBoost, Random Forest, Generalized Linear Modeling (GLM with Elastic Net), K-Means, PCA, Generalized Additive Models (GAM), RuleFit, Support Vector Machine (SVM), Stacked Ensembles, Automatic Machine Learning (AutoML), etc.

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Stacked Ensemble: enable using previously persisted base models #7949

Open exalate-issue-sync[bot] opened 1 year ago

exalate-issue-sync[bot] commented 1 year ago

The goal is to make sure that a user can use persisted model (saved to disk as binary model or MOJO and loaded back into H2O) as a base model.

Investigate what information is possibly lost due to persisting a base model. (e.g. CV preds, CV models?)
Rethink what checks are appropriate for which scenario (super learning/blending).
Fix potential issues.

h2o-ops commented 1 year ago

JIRA Issue Migration Info

Jira Issue: PUBDEV-7690 Assignee: Tomas Fryda Reporter: Tomas Fryda State: Open Fix Version: N/A Attachments: N/A Development PRs: N/A