Week 46: Support Vector Machines and Project 3.
Contents
Overview of week 46
Support Vector Machines, overarching aims
Hyperplanes and all that
What is a hyperplane?
A \( p \)-dimensional space of features
The two-dimensional case
Getting into the details
First attempt at a minimization approach
Solving the equations
Code Example
Problems with the Simpler Approach
A better approach
A quick Reminder on Lagrangian Multipliers
Adding the Multiplier
Setting up the Problem
The problem to solve
The last steps
A soft classifier
Soft optmization problem
Kernels and non-linearity
The equations
The problem to solve
Different kernels and Mercer's theorem
The moons example
Mathematical optimization of convex functions
How do we solve these problems?
A simple example
Back to the more realistic cases
Support vector machines for regression
Support vector machines for regression
Material will be added here.
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