Week 6 — Lesson 2: Random forests, many trees vote

3 min

One deep tree memorises the NorthPeak training rows. Change a few rows and its first question switches to another column; its predictions on new months jump around. A random forest fights that with numbers: many trees, each grown on a random sample of rows and columns, voting together. On July to September, months the models never saw, one unlimited tree scored an AUC of 0.726 and a forest of 100 trees scored 0.924. This lesson explains why the trees must disagree, and what the vote buys.

Preview — the rest of the lesson is for enrolled readers.

Already enrolled with a code?

Your access is tied to your account, not to this link. Sign in with the same email you used in class: your course is waiting, no need to enter the code again.

This lesson is part of the “Week 6 — Model selection and validation” module

The first modules of the course are open to everyone. For the rest you have three options: buy this course once and for all, subscribe, or enter the code handed out in class.

Back to the outline