Lesson 15 of 21 · Part IV, SVMs and ensembles

Bias-variance and ensembles

The expected error over training sets decomposed into variance, bias² and noise, the role of λ in the trade-off, then ensembles: committees, bagging and boosting, and a note on feature selection.

7 figures to manipulate.

In this lesson

• The idea
• Analysis in regression
• Bias, variance and regularization
• Ensemble learning
• Feature selection (outline)

Other lessons

SVMs and kernels — practical aspects and a critical view · Convolutional neural networks (CNN) · All lessons

Notes by Fabio Piscitelli — Machine Learning (654AA), Prof. Alessio Micheli, University of Pisa, a.y. 2026/27.