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Visualizing Bagged Trees as Approximating Borders

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.

Visualizing Bagged Trees as Approximating Borders, Part 1

Visualizing Bagged Trees, Part 2

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.

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