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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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In GBM, monotone_constraints is available for Bernoulli #9243

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

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

In GBM, the description for monotone_constraints states: Also note that this option can only be used when distribution="gaussian".

A comment in https://github.com/h2oai/h2o-3/pull/3338 states: "It is only allowed for Gaussian in this PR, Bernoulli is implemented in another PR"

Update the docs to reflect this info.

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

Angela Bartz commented: In the Flow and GBM chapters, added that monotone_constraints can be used when the distribution is set to bernoulli. Previously, this stated that monontone_constraints was only available for gaussian distributions.

Pull request submitted to master.

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

Angela Bartz commented: Pull request merged into master.

h2o-ops commented 1 year ago

JIRA Issue Migration Info

Jira Issue: PUBDEV-6381 Assignee: Angela Bartz Reporter: Angela Bartz State: Resolved Fix Version: 3.24.0.1 Attachments: N/A Development PRs: Available

Linked PRs from JIRA

https://github.com/h2oai/h2o-3/pull/3397