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Data Analysis and Machine Learning: Support Vector Machines
Contents
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
A better approach
A quick reminder on Lagrangian multipliers
Adding the muliplier
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
Code Example
Multiclass problems and regression with SVMs
Multiclass problems and regression with SVMs
This material will be added later.
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