SVM using Interior point methods

image source: https://en.wikipedia.org/wiki/Support-vector_machine

Introduction

Support vector machine is used for classification in machine learning. The goal is to classify data while maximizing the margin between the data and the classifier.

Interior-point methods is used for solving convex optimization problems. Two of the interior point methods are: Barrier method, Primal-Dual Interior Point method. For more information about these methods you can refer to chapter 11 of Convex Optimization book by Stephen Boyd.

Implementation

The code can be found on github. In this project the SVM with RBF kernel is implemented.

To be continued …