Issues

R: Explaination related functions should check for presence of ggplot2 of a required version

'H2OAutoML' object has no attribute 'explain'

Remove newdata arg from hidden .plot_varimp function in R

Expose input -> output column mapping in Target Encoder

Kubernetes operator for H2O-3

POC Add multi-GPU support on single node for XGBoost

XGBoost: Allow CV to use multiple GPUs (on a single node)

Stacked Ensembles don't respect the schema of the base models

when loading the same data with the same query - it is overwriting the data in memory (changing the frame in memory)

Import_sql_select, import_sql_table: fetch mode distributed has data discrepancy then single mode or import_file

Add 'without quotes' option for header to exportFile

Mention ONNX support in our documentation

provide ROC curve and data for it

Add information about how early stopping is used to tune models in the User Guide

Create better learning curve function in R and Python

Get original categorical features from the model for h2o.varimp_heatmap()

Add "without quotes" option to ExportFile method

Show missing values in numeric PDP plots

Allow h2o.varimp() to use ggplot2 in addition to base R plotting

Fill in Variable Importance user guide page with info about non-tree-based models

Add a `topbasemodel` attribute to AutoML

Add support for list of models to the h2o.get_leaderboard function

Change empty list defaults to NULL for arguments in R API

Replace algo IDs with human readable names in AutoML