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.
We want to be able to have each tree in the ensemble sample from the full training dataset, but not just with a global sampling factor (sample_rate), but a per-class specific sampling rate. This can help for imbalanced datasets.
We want to be able to have each tree in the ensemble sample from the full training dataset, but not just with a global sampling factor (sample_rate), but a per-class specific sampling rate. This can help for imbalanced datasets.
float[] sample_rate_per_class