Algorithms

This section provides an overview of each algorithm available in H2O. For detailed information about the parameters that can be used for building models, refer to Appendix A - Parameters.

Common

• Quantiles
• Early Stopping

Supervised

• Cox Proportional Hazards (CoxPH)
• Deep Learning (Neural Networks)
• Distributed Random Forest (DRF)
• Generalized Linear Model (GLM)
• Gradient Boosting Machine (GBM)
• Naïve Bayes Classifier
• Stacked Ensembles
• Support Vector Machine (SVM)
• XGBoost

Unsupervised

• Aggregator
• Generalized Low Rank Models (GLRM)
• Isolation Forest
• K-Means Clustering
• Principal Component Analysis (PCA)

Miscellaneous

• Word2vec

MOJO Models

• MOJO Models