O'Reilly logo

Practical Data Analysis by Hector Cuesta

Stay ahead with the world's most comprehensive technology and business learning platform.

With Safari, you learn the way you learn best. Get unlimited access to videos, live online training, learning paths, books, tutorials, and more.

Start Free Trial

No credit card required

Chapter 8. Working with Support Vector Machines

The support vector machine (SVM) is a powerful classification technique. In this chapter, we will provide the reader with an easy way to get acceptable results using SVM. We will perform dimensionality reduction of the dataset and we will produce a model for classification.

The theoretical foundation of SVM lies in the work of Vladimir Vapnik and the theory of statistical learning developed in the 1970s. The SVMs are highly used in pattern recognition of Time Series, Bioinformatics, Natural Language Processing, and Computer Vision.

In this chapter, we will use the mlpy implementation of LIBSVM, which is a widely used library for SVM with several interfaces and extensions for languages such as Java, ...

With Safari, you learn the way you learn best. Get unlimited access to videos, live online training, learning paths, books, interactive tutorials, and more.

Start Free Trial

No credit card required