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.
It would be nice to see what metrics are available for a specific problem type / instantiated model.
for example, if you ran a regression problem it would be nice to do:
{code} model.available_metrics()
["logloss","mse","rmse","mae","rmsle","deviance"]
{code}