Using H2O(-3) for hyperparameter optimization with non-H2O classifiers

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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Using H2O(-3) for hyperparameter optimization with non-H2O classifiers #12557

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

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

Does H2O(-3) library able to do meta-learning (the hyperparameter optimization)?

via e.g. Random Search?
with non-H2O classifiers (i.e. classifiers, e.g. kNN, C4.5, AdaBoostM1, SMO, etc., written in Java from another library)?

Can I use H2O for this purpose in Java? If so, how can I integrate it into own Java code?

What are the most significant interfaces/classes for the integration and the following meta-learning? Can you please provide some examples.

hasithjp commented 1 year ago

JIRA Issue Migration Info

Jira Issue: PUBDEV-5701 Assignee: Michal Kurka Reporter: TO State: Open Fix Version: N/A Attachments: N/A Development PRs: N/A