Understanding StochTree

Stochastic tree models are a powerful addition to your modeling toolkit. As with many machine learning methods, understanding these models in depth is an involved task.

We provide some high-level explanations of the core concepts and models supported by stochtree, with pointers to specific software settings / config and to the underlying literature.

• Overview of Stochastic Trees: high-level intro to stochastic decision tree ensembles
• BART: review of the supervised learning models supported by stochtree’s BART interface in R and Python
• BCF: review of the causal models supported by stochtree’s BCF interface in R and Python