New versions of H2O-3 and Sparkling Water available

Dear H2O Community,

#H2OWorld is on Monday and we can’t wait to see you there! We’ll also be live streaming the event starting at 9:25am PST. Explore the agenda here.

Today we’re excited to share that new versions of H2O-3 and Sparkling Water are available.

We invite you to download them here:
https://www.h2o.ai/download/

H2O-3.16
– MOJOs are now supported for Stacked Ensembles.
– Easily specify the meta-learner algorithm type that Stacked Ensemble should use. This can be AUTO, GLM, GBM, DRF or Deep Learning.
– GBM, DRF now support custom evaluation metrics.
– The AutoML leaderboard now uses cross-validation metrics (new default).
– Multiclass stacking is now supported in AutoML. Removed the check that caused AutoML to skip stacking for multiclass.
– The Aggregator Function is now exposed in the Python/R client.
– Support for Python 3.6.

Detailed changes and bug fixes can be found here:
https://github.com/h2oai/h2o-3/blob/master/Changes.md

Sparkling Water 2.0, 2.1, 2.2
– Support for H2O Models into Spark python pipelines.
– Improved handling of sparse vectors in internal cluster.
– Improved stability of external cluster deployment mode.
– Includes latest H2O-3.16.0.2.

Detailed changes and bug fixes can be explored here:
2.2 – https://github.com/h2oai/sparkling-water/blob/rel-2.2/doc/CHANGELOG.rst
2.1 – https://github.com/h2oai/sparkling-water/blob/rel-2.1/doc/CHANGELOG.rst
2.0 – https://github.com/h2oai/sparkling-water/blob/rel-2.0/doc/CHANGELOG.rst

Hope to see you on Monday!

The H2O.ai Team