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MAI4CAREU - Machine Learning: Trees and Forests

In MAI612 Lecture 6, the spotlight shines on Decision Trees and Ensemble Learning, unravelling the intricacies of these powerful techniques. Students embark on a journey to understand the inner workings of decision tree models, delving into concepts of entropy and information gain for training.

The University of Cyprus's MSc Artificial Intelligence is part of the Master programmes in Artificial Intelligence 4 Careers in Europe (MAI4CAREU). One of Master's programme's courses, MAI612 - Machine Learning is split up into several lectures. Taught by Vassilis Vassiliades, PhD, the sixth lecture of the MAI612 - Machine Learning course focuses on Trees and Forests.

Learning outcomes

  • How decision tree models work
  • How to train decision trees using the concepts of entropy and information gain
  • How to use continuous variables in decision trees
  • Classification and regression trees
  • Why ensembles of models can achieve lower generalization errors
  • Ensemble methods such as bagging, random forests, boosting, XGBoost and stacking

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Additional information

Target audience
Digital skills for ICT professionals and other digital experts.
Geographic scope - Country
Austria
Belgium
Bulgaria
Cyprus