The Six Steps to Boosted Trees

BigML is bringing Boosted Trees to our ever-growing suite of supervised learning techniques. Boosting is a variation on ensembles that aims to reduce bias, potentially leading to better performance than Bagging or Random Decision Forests. In our first blog post of this series of six posts about Boosted Trees, we saw a gentle introduction to Boosted Trees to get some context about what this new resource is and how it can help you solve your classification and regression problems. This post will take us further, into the detailed steps of how to use boosting with BigML. To learn from our data, we must first upload it.