Machine Learning with SAS Viya

Chapter 11: Support Vector Machines

Introduction

Support Vector Machine Algorithm

Choosing the Best Hyperplane

What Are the Support Vectors?

Demo 11.1: Building a Support Vector Machine Based on Default Settings

Improve the Model and Optimizing Complexity

The Optimization Problem

Details: The Optimization Problem

Details: The Solution

Demo 11.2: Changing the Methods of Solution for a Support Vector Machine

The Kernel Trick

Details: Dot Products in Feature Spaces Are Mathematically Difficult to Calculate

Details: The Solution

Model Studio: Kernel Parameters

Model Interpretability

Model Interpretability in Model Studio

Demo 11.3: Changing the Kernel Function for a Support Vector Machine and Adding Model Interpretability

Regularize and Tune Hyperparameters ...