I am learning about random forest and found this video https://www.youtube.com/watch?v=gdnIqGbqiYs&list=UUb9svouAi1XHRqlOs8LXbBg very useful.
The first 8 minutes explain how to visualise how the feature space is partitioned as the tree is populated during training. In the video however, the partitioning is only explained with respect to two feature vectors throughout the entire tree. It was pretty easy to understand how the feature space is partitioned for two features, as the feature space plots feature 1 vs feature 2.
However if I have multiple features selected at random to be used in any node of a given tree, how do I visualise the feature space and how it is partitioned? For example if one branch contains 5 nodes, with 5 features being selected before reaching the leaf node, how is the feature space partitioned to include all 5 features?
