H2O v3.32.0.1 Release Notes
-
π Download at: http://h2o-release.s3.amazonaws.com/h2o/rel-zermelo/1/index.html
π Bug
π [PUBDEV-7667] - Fixed StackedEnsembleβs retrieval of the seed parameter value. [PUBDEV-7746] - Deserialization values of MOJO ModelParameter now work when the Value Type is int[]. π [PUBDEV-7760] - H2O no longer uses lazy-loading for sequential zip parse. β‘οΈ [PUBDEV-7762] - Updated model_type argument names for Rulefit in R.
π New Feature
[PUBDEV-7241] - Quantile distributions added to monotone constraints. [PUBDEV-7319] - TargetEncoder integrated into ModelBuilder. [PUBDEV-7755] - Python client no longer instructs the user to declare a root handler in library mode. [PUBDEV-7791] - Hostname used as certificate alias to lookup machine-specific certificate allowing Hadoop users to connect to Flow over HTTPS. [PUBDEV-7796] - Added the model explainability interface for H2O models and AutoML objects in both R & Python. [PUBDEV-7720] - Added the RuleFit algorithm for interpretability. [PUBDEV-7808] - Implemented a basic HELM chart.
Task
[PUBDEV-7763] - Rulefit model added to algorithm section of UserGuide. [PUBDEV-7786] - Added an Explainability page to the User Guide outlining the new
h2o.explain()
andh2o.explain_row()
functions. β‘οΈ [PUBDEV-7804] - Updated the AutoML User Guide page to include the new Explainability and Preprocessing sections.π Improvement
π [PUBDEV-5932] - Added support for Python 3.7+. [PUBDEV-7717] - Exposes names of score0 output values in MOJO. [PUBDEV-7730] - Added function to plot a Precision Recall Curve. [PUBDEV-7740] - RuleFit model represented by the set of rules obtained from trees during training. π [PUBDEV-7765] - Performance improved for exporting a Frame to CSV. [PUBDEV-7769] - GPU backend allowed in XGBoost when running multinode even when
build_tree_one_node
is enabled. β‘οΈ [PUBDEV-7787] - Updated all URLs in R package to use HTTPS. β¬οΈ [PUBDEV-7790] - Upgraded to XGBoost 1.2.0.Technical task
π [PUBDEV-7366] - Added cross-validation to GAM allowing users to find the best alpha/lambda values when building a GAM model. π [PUBDEV-7672] - Added TargetEncoder support for multiclass problems. π [PUBDEV-7743] - Added new TargetEncoder parameter that allows users to remove original features automatically. π [PUBDEV-7778] - Implemented minimal support for TargetEncoding in AutoML.
π Docs
β‘οΈ [PUBDEV-7541] - Updated the descriptions of AutoML in R & Python packages. π [PUBDEV-7781] - Made the default for
categorical_encoding
in XGBoost explicit in the documentation. β‘οΈ [PUBDEV-7811] - Updated the import datatype section of the Python FAQ in the User Guide. [PUBDEV-7815] - Updated the default values formin_rule_length
andmax_rule_length
on the RuleFit page of the User Guide. β‘οΈ [PUBDEV-7816] - Updated thevalidation_frame
definition for unsupervised algorithms in the User Guide.