H2O is an Open Source, Distributed, Fast & Scalable Machine Learning Platform: Deep Learning, Gradient Boosting (GBM) & XGBoost, Random Forest, Generalized Linear Modeling (GLM with Elastic Net), K-Means, PCA, Generalized Additive Models (GAM), RuleFit, Support Vector Machine (SVM), Stacked Ensembles, Automatic Machine Learning (AutoML), etc.
In [PUBDEV-3835|https://0xdata.atlassian.net/browse/PUBDEV-3835], [~accountid:557058:2ceb7f2b-e7ca-465c-8e82-c046991100be] added the following feature: GLM will now produce standard errors for predictions (as an extra column called StdErr) if it the model has been built with p-values.
As part of this, we should now be able to access the Variance-Covariance matrix, and so we should add the ability to store and access/retrieve this matrix in a GLM model (when built with p-values).
In [PUBDEV-3835|https://0xdata.atlassian.net/browse/PUBDEV-3835], [~accountid:557058:2ceb7f2b-e7ca-465c-8e82-c046991100be] added the following feature: GLM will now produce standard errors for predictions (as an extra column called StdErr) if it the model has been built with p-values.
As part of this, we should now be able to access the Variance-Covariance matrix, and so we should add the ability to store and access/retrieve this matrix in a GLM model (when built with p-values).