Lesson 14 of 21 · Part IV, SVMs and ensembles

SVMs and kernels — practical aspects and a critical view

Strengths and weaknesses of SVMs, the results on the two-class problem, the critical role of C and of the kernel parameters, the myths to debunk and kernel methods as similarity measures.

4 figures to manipulate.

In this lesson

• Main characteristics
• Results
• SVMs in practice
• Kernel methods

Other lessons

Support Vector Machines · Bias-variance and ensembles · All lessons

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