Background | Software requirements and installation | Setup dataset | Review available models | Fit individual models | Fit multiple models | Predict on new data | Fit ensemble with external cross-validation | Customize a model hyperparameter | Test algorithm with multiple hyperparameter settings | Multicore parallelization | Weight distribution for SuperLearner | Feature selection (screening) | Optimize for AUC | XGBoost hyperparameter exploration | Troubleshooting | References