Mastering Azure Machine Learning - Second Edition

Chapter 9: Building ML Models Using Azure Machine Learning

In the previous chapters, we learned about datasets, preprocessing, feature extraction, and pipelines in Azure Machine Learning. In this chapter, we will use the knowledge we have gained so far to create and train a powerful tree-based ensemble classifier.

First, we will look behind the scenes of popular ensemble classifiers such as random forest, XGBoost, and LightGBM. These classifiers perform extremely well in practical real-world scenarios, and all are based on decision trees under the hood. By understanding their main benefits, you will be able to spot problems that can be solved with ensemble decision tree classifiers easily.

We will also learn the difference between gradient boosting ...