© Alok Kumar and Mayank Jain 2020
A. Kumar, M. JainEnsemble Learning for AI Developershttps://doi.org/10.1007/978-1-4842-5940-5_3

3. Mixing Models

Alok Kumar1  and Mayank Jain1
Gurugram, India

In Chapter 2, you learned how to divide and mix training data in different ways to build ensemble models, which perform better than a model that was trained on an undivided dataset.

In this chapter, you learn different ways to assemble. Unlike the mixing training data approach, the mixing models approach uses the same dataset in different machine learning models and then combines the results in different ways to get better performing models.

First, let’s look at this chapter’s goals.
  • Introduce and explain mixing models based on ensemble

  • Introduce voting ensembles ...

Get Ensemble Learning for AI Developers: Learn Bagging, Stacking, and Boosting Methods with Use Cases now with O’Reilly online learning.

O’Reilly members experience live online training, plus books, videos, and digital content from 200+ publishers.