Step-by-Step Guide to leave-one-person-out Cross Validation with Random Forests in Python

I have received a number of requests for how to implement leave-one-person-out cross validation with random forests. I refined my methods into a function and published it on the Digital Biomarker Discovery Pipeline (DBDP). If you want to implement this cross validation in your own work with random forests, please visit the repository on the DBDP GitHub. The ‘how-to’ of using the function is well documented and can be easily implemented with only one line in a number of projects.