The bagged trees algorithm is a commonly used classification method. By resampling our data and creating trees for the resampled data, we can get an aggregated vote of classification prediction. In this blog post I will demonstrate how bagged trees work visualizing each step.
Conclusion: Other tree aggregation methods differ in how they grow trees and they may compute weighted average. But in the end we can visualize the result of a algorithm as borders between classified sets in a shape of connected perpendicular segments, as in this 2-dimensional case. As for higher dimensions these became multidimensional rectangular pieces of hyperplanes which are perpendicular to each other.