Learn about advanced concepts in support vector machines (SVMs) in this comprehensive lecture. Explore soft margins, slack variables, and penalty terms to handle non-linearly separable data. Discover how to extend SVMs to multi-class problems using pairwise comparison and continuous ranking techniques. Gain insights into the practical applications of SVMs for complex classification tasks.
Overview
Syllabus
Introduction
Problem
Soft Margin
Slack Variables
Penalty Term
Soft Margins
Multiple Classes
Pairwise Comparison
Continuous Ranking
MultiClass Margin
Taught by
Pascal Poupart
