Issues

Add Constructor to PreviewParseWriter with Domains as Parameter

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

Update ggplot2 required version in R package to 3.3.0

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

'H2OAutoML' object has no attribute 'explain'

Finalization API with Leaving Frames Locked

Create better learning curve function in R and Python

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

GLM Generic model doesn't provide varimp function

GLM: ArrayIndexOutOfBoundsExceptiom after training CV models

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

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

Target Encoding: support feature interaction

Feature Request:uplift trees

create similar feature on Native XGBoost: feature_interaction_constraint

Expose input -> output column mapping in Target Encoder

pretty up multinomial/classification dataset generation to make it useful to generate syn dataset.

Fix GLMGradientTask.computeNumericEtas for all GLM families except Binomial

Verify How Early Stopping in GLM Compares to Other Models

clean up python compare_frame to compare_frame_local. There is no need for both.

Make sure GLM cross-validation works properly with Lambda_search=True or False and other settings

Use loading_name to allow users to choose name for X frame key if they want.

Generate synthetic datasets from GLM/Deeplearning/GBM models for GLM/Deeplearning/GBM

Add parameter lambda_best to GLM output parameter