Issues

Update ggplot2 required version in R package to 3.3.0

Add parameter lambda_best to GLM output parameter

Add `rule_generation_netrees` parameter to rulefit page

Missing syntax highlight Random Grid search Python example

Add parameter lambda_min to GLM output parameter

CV Frames have all the same number of rows as training frame

3.32.0.1 Release Notes

CoxPH performance fails, if factor used as event_column

Add code examples for all the new explainability plotting functions in Python

Add code examples for all the new explainability plotting functions in R

XGBoost Fails With AssertionError When Specifying Custom Fold Column

Speed up model_summary computations in AutoML Stacked Ensembles in R

Update `validation_frame` definition for unsupervised algorithms

Update Rulefit page default values

Update Python FAQ import datatype in UserGuide

Create HELM charts for H2O-3

Update AutoML user guide page with new Explainability and Preprocessing sections

Model explainability interface for H2O models and AutoML objects in R/Python

GLM: ArrayIndexOutOfBoundsExceptiom after training CV models

Support per-node certificates on Hadoop in a global JKS

Uprgrade to XGBoost 1.2.0

Add an Explainability page in the User Guide

GLM raises ArrayIndexOutOfBoundsException with CV+lambda_search+alphas+categorical columns

Categorical_encoding default/auto one_hot_internal to be explicit in the documentation