Random Forests in Chapel
Benjamin Albrecht · 2020
This talk will present the ongoing work of developing a Chapel implementation of Random Forest, a popular ensembling learning method utilized both for predictive modeling and feature selection. Language features in Chapel make it possible to easily express shared-memory and distributed-memory implementations of this algorithm. Furthermore, Chapel's built-in python interoperability functionality made it easier to implement a python front-end, making it accessible to a language popular among data scientists.