Google AdaNet is a Lightweight, AutoML Framework for Building Ensemble Learning Models

The new framework incorporates some cutting edge ideas for AutoML systems.

Source: https://www.kdnuggets.com/2021/02/microsoft-explores-three-key-mysteries-ensemble-learning.html

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Ensemble learning is a deep learning technique that combines multiple machine learning models into an ensemble that can outperform each of the individual models. The main thesis behind ensemble learning is rooted in the famous No-Free-Lunch-Theorem(NFLT) that states than given all possible data distributions in an environment, we can’t expect any model to do better than random. In other words, models that might seem like the perfect solution for a problem might perform poorly given a change in the data distribution. If that’s the case, why not to…