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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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Documentation: Add subsections for Solver and Family/Link in GLM section of UG, fix Handling of Categorical Values #10690

Closed exalate-issue-sync[bot] closed 1 year ago

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

In the GLM section of the User Guide, add subsections for Solver and for Family/Link. The solver, family, and link parameters can then point to these sections.

In addition, while working on this topic, update the section regarding Handling of Categorical Values. It is out of date includes documentation for a flag that no longer exists (use_all_factor_levels). See https://groups.google.com/forum/#!topic/h2ostream/fGI-Hzdm15o for reference.

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

Angela Bartz commented: In the GLM section of the UG, added subsections describing Solvers and describing Family and Link Functions. Updated the section on handling categorical variables. This is now a subsection under a heading, “Classification and Regression.” Also added another subsection describing handling of numeric values. Finally, added a reference to a paper regarding the new quasibinomial family.

Pull request 604 submitted.

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

Angela Bartz commented: Pull request merged.

h2o-ops commented 1 year ago

JIRA Issue Migration Info

Jira Issue: PUBDEV-3792 Assignee: Angela Bartz Reporter: Angela Bartz State: Resolved Fix Version: N/A Attachments: Available (Count: 1) Development PRs: Available

Linked PRs from JIRA

https://github.com/h2oai/h2o-3/pull/604

Attachments From Jira

Attachment Name: glm.rst Attached By: Angela Bartz File Link:https://h2o-3-jira-github-migration.s3.amazonaws.com/PUBDEV-3792/glm.rst