Applying CART models to risk analysis

I had a great time presenting a lecture on the application of CART machine learning models to risk analysis at the Civil Aviation University of China yesterday. Many thanks to my hosts. I look forward to further opportunities for collaboration in the applications of advanced data analytics to questions on risk analysis and management.

CART models have several valuable characteristics for risk analysis including learning more effectively from incomplete data, identifying critical thresholds, identifying conditionally important variables, and interpretability. I have employed CART models and random forest models in a variety of risk-related applications from mine worker safety to nanoparticle toxicity, and always looking for more that they can do.