Using Hybrid Machine Learning Models

Marcelo Guarido, Daniel O. Trad, David J. Emery

For this lab, we will go through the work from Khan et al (2020), that used a hybrid model to forecast the energy consumption of renewable and non-renewable power sources, and we will "reproduce" part of their methodology (the modeling part). We will show different ways to combine trained machine learning models to create a more powerful and more robust model using Python libraries such as Scikit-Learn and Mlxtend.