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Decision Trees
Introduction
Decision Tree
Where To Partition?
Information Gain
Another Look At Our Decision Tree
The Problem of Perturbations
Going Beyond A Single Tree
Code with Python
Summary
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Decision TreesGoing Beyond A Single Tree

Reading time: ~5 min

To finish, put the steps for growing a tree in order.

Keep the cut with the largest information gain
Work out the entropy of the box
Repeat inside each new box until it is pure or deep enough
Try every cut on every feature

If one tree is this sensitive, how do we fix it? Surprisingly, with more randomness. Grow many trees, each on a slightly different random sample of the data, and let them vote. One tree may be fooled by a faulty scale, but a crowd of different trees is rarely fooled in the same way. This idea leads to one of the most successful methods in classical machine learning: .

Sina