May 1, 2024

In the final episode of this mini-series, Shea and Anders cover the other common tree-based ensemble model, the Gradient Boosting Machine. Like Random Forests, GBMs make use of a large number of decision trees, but they use a “boosting” approach that cleverly makes use of “weak learners” to incrementally...

Apr 10, 2024

Building on the discussion of individual decision trees in the prior episode, Shea and Anders shift to one of today’s most popular ensemble models, the Random Forest. At first glance, the algorithm may seem like a brute force approach of simply running hundreds or thousands of decision trees, but it leverages the...

Mar 20, 2024

Shea and Anders dive into tree-based algorithms, starting with the most fundamental variety, the single decision tree. We cover the mechanics of a decision tree and provide a comparison to linear models. A solid understanding of how a decision tree works is critical to fully grasp the nuances of the more powerful...

Feb 28, 2024

This is the first episode in a new mini-series, “Return to Trees”. In this series, Shea and Anders will be covering tree-based algorithms, including single decision trees, Random Forests, and Gradient Boosting Machines. In this episode, we discuss the rationale for re-visiting these models, which were covered in...

May 11, 2023

The SOA launched a new initiative, the emerging topics community, as a pilot in 2021.  In this short discussion, we explain what the emerging topics community is, how it is structured and what benefits it brings to the SOA community.  Information is also provided on how anyone can volunteer and contribute.

Joe Alaimo...