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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.
http://h2o.ai
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Add a max_depth_noise_sigma parameter to RF and GBM #10261

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

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

Add the ability to add noise to the max_depth parameter in RF and GBM via a new max_depth_noise_sigma argument that defaults to 0. If this is greater than zero, it will sample the max_depth value for each tree from a Gaussian with mean = max_depth and sigma = max_depth_noise_sigma.

This will result in trees grown with different values of max_depth, adding greater variability among the trees in the ensemble.

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

Tom Kraljevic commented: I wonder if it makes more sense to allow providing a metadata description of the forest, so you can specify the details of each tree one-by-one in full detail.

Then parameters like this can be layered on top.

h2o-ops commented 1 year ago

JIRA Issue Migration Info

Jira Issue: PUBDEV-3349 Assignee: New H2O Bugs Reporter: Erin LeDell State: Open Fix Version: N/A Attachments: N/A Development PRs: N/A