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.
Consider turning off early stopping in the default DRF and XRT models in AutoML since we only have 50 trees. First, evaluate on some datasets and see how this affects performance. Let's benchmark to see if this is a good idea or not.
One issue here is that the default score iteration is not an even number -- another option is to change score_tree_interval to 2 or 5.
Consider turning off early stopping in the default DRF and XRT models in AutoML since we only have 50 trees. First, evaluate on some datasets and see how this affects performance. Let's benchmark to see if this is a good idea or not.
One issue here is that the default score iteration is not an even number -- another option is to change score_tree_interval to 2 or 5.