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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Docs: Add monotonicity constraints to list of GBM parameters #12978

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

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

PUBDEV-5865 adds new monotone_constraints option to GBM. Similar to XGBoost:

monotone_constraints: A mapping representing monotonic constraints. Use +1 to enforce an increasing constraint and -1 to specify a decreasing constraint. Note that constraints can only be defined for numerical columns.

Also add link to new monotonicity constraints demo in https://github.com/h2oai/h2o-3/tree/master/h2o-py/demos

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

Angela Bartz commented: Pull request submitted to rel-xia.

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

Angela Bartz commented: Pull request merged into rel-xia.

hasithjp commented 1 year ago

JIRA Issue Migration Info

Jira Issue: PUBDEV-6148 Assignee: Angela Bartz Reporter: Angela Bartz State: Resolved Fix Version: 3.22.0.3 Attachments: N/A Development PRs: Available

Linked PRs from JIRA

https://github.com/h2oai/h2o-3/pull/3161