Chapter 8. Creating Ensemble Models

A group of people have the ability to take better decisions than a single individual, especially when each group member comes in with their own biases. The ideology is also true for machine learning.

When single algorithms are not capable to generate the true prediction function, then ensemble machine-learning methods are used. When there is more focus on the performance of the model rather than the training time and the complexity of the model, then ensemble methods are preferred.

In this chapter, we will discuss:

  • What is ensemble learning?
  • Constructing ensembles.
  • Combination strategies.
  • Boosting, bagging, and injecting randomness.
  • Random forests.

What is ensemble learning?

Ensemble learning is a machine learning method ...

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