:quality(75))
- H2O Release 3.18, named Wolpert after Stacked Ensembles inventor David Wolpert, added support for XGBoost multi-node training in H2O.
- H2O Release 3.18 let users exclude specific algorithms during an AutoML run and pass a customized metalearner or a seed parameter into Stacked Ensemble.
- H2O Release 3.18 let GLM users specify a list of interaction terms to include or exclude when building a model.
- H2O Release 3.18 fixed a bug that caused XGBoost MOJOs to fail unless users manually added the Commons Logging dependency.
- H2O Release 3.18 fixed a bug that caused XGBoost binary model save and load operations to fail.
Wolpert Release (H2O 3.18)
There’s a new major release of H2O and it’s packed with new features and fixes!
We named this release after David Wolpert, who is famous for inventing Stacking (aka Stacked Ensembles). Stacking is a central component in H2O AutoML, so we’re very grateful for his contributions to machine learning! He is also famous for the “No Free Lunch” theorem, which generally states that no single algorithm will be the best in all cases. In other words, there’s no magic bullet. This is precisely why stacking is such a powerful and practical algorithm — you never know in advance if a Deep Neural Network, or GBM or Random Forest will be the best algorithm for your problem. When you combine all of these together into a stacked ensemble, you are guaranteed to benefit from the strengths of each of these algorithms. You can read more about Dr. Wolpert and his work here.
Distributed XGBoost
AutoML & Stacked Ensembles
Highlights
Below is a list of some of the highlights from the 3.18 release. As usual, you can see a list of all the items that went into this release at the Changes.md file in the h2o-3 GitHub repository.
New Features:
- PUBDEV-4652 – Added support for XGBoost multi-node training in H2O
- PUBDEV-4980 – Users can now exclude certain algorithms during an AutoML run
- PUBDEV-5086 – Stacked Ensemble should allow user to pass in a customized metalearner
- PUBDEV-5224 – Users can now specify a seed parameter in Stacked Ensemble
- PUBDEV-5204 – GLM: Allow user to specify a list of interactions terms to include/exclude
Bugs:
- PUBDEV-4585 – Fixed an issue that caused XGBoost binary save/load to fail
- PUBDEV-4593 – Fixed an issue that caused a Levenshtein Distance Normalization Error
- PUBDEV-5133 – In Flow, the scoring history plot is now available for GLM models
- PUBDEV-5195 – Fixed an issue in XGBoost that caused MOJOs to fail to work without manually adding the Commons Logging dependency
- PUBDEV-5215 – Users can now specify interactions when running GLM in Flow
- PUBDEV-5315 – Fixed an issue that caused XGBoost OpenMP to fail on Ubuntu 14.04
Documentation:
- PUBDEV-5311 – The H2O-3 download site now includes a link to the HTML version of the R documentation
Download here: http://h2o-release.s3.amazonaws.com/h2o/latest_stable.html