Boosting and AdaBoost for Machine Learning

Last Updated on August 15, 2020

Boosting is an ensemble technique that attempts to create a strong classifier from a number of weak classifiers.

In this post you will discover the AdaBoost Ensemble method for machine learning. After reading this post, you will know:

• What the boosting ensemble method is and generally how it works.
• How to learn to boost decision trees using the AdaBoost algorithm.
• How to make predictions using the learned AdaBoost model.
• How to best prepare your data for use with the AdaBoost algorithm

This post was written for developers and assumes no background in statistics or mathematics. The post focuses on how the algorithm works and how to use it for predictive modeling problems. If you have any questions, leave a comment and I will do my best to answer.

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