Ensemble Machine Learning Techniques 2.4: Ensemble Learning for Regression

This video tutorial covers simple ensemble learning techniques for regression, focusing on averaging and weighted averaging. Averaging combines regression models for continuous outputs and can be applied to classification by averaging output probabilities. An example of movie rating aggregation is provided. Weighted averaging assigns different weights to models based on their importance, demonstrated through a movie rating example. The video concludes with a summary and a preview of implementing these techniques in Python in the next video.

What criteria can be used to decide the weights assigned to different models?

What is the significance of model accuracy in the context of weighted averaging?