Machine Learning from the Woods: Exploring Tree-Based Ensemble Models in Python

Python is a hot topic right now. So is machine learning. And ensemble models.

Put the three together, and you have a mighty combination of powerful technologies.

This article provides an extensive overview of tree-based ensemble models and the many applications of Python in machine learning. Read on to learn why these models are the perfect solution for numerous machine learning problems.

Here’s what we’re going to cover:

• First, I’ll give you some basic theory behind three ensemble models: random forests, AdaBoost, and gradient tree boosting.
• Next, I’ll teach you how to implement those ensemble models using one of the most popular Python libraries for machine learning: scikit-learn.
• Lastly, I’ll show you how to improve the out-of-the-box performance of your ensemble models.