User Guide# Training and Evaluating Machine Learning Models Shared Library Imports Random Forest Classification and Accuracy metrics UMAP and Trustworthiness metrics DBSCAN and Adjusted Random Index Linear regression and R^2 score Pickling Models for Persistence Single GPU Model Pickling Distributed Model Pickling Exporting cuML Random Forest models for inferencing on machines without GPUs Using cuML on CPU, GPU, or both